blob_id stringlengths 40 40 | directory_id stringlengths 40 40 | path stringlengths 2 327 | content_id stringlengths 40 40 | detected_licenses listlengths 0 91 | license_type stringclasses 2
values | repo_name stringlengths 5 134 | snapshot_id stringlengths 40 40 | revision_id stringlengths 40 40 | branch_name stringclasses 46
values | visit_date timestamp[us]date 2016-08-02 22:44:29 2023-09-06 08:39:28 | revision_date timestamp[us]date 1977-08-08 00:00:00 2023-09-05 12:13:49 | committer_date timestamp[us]date 1977-08-08 00:00:00 2023-09-05 12:13:49 | github_id int64 19.4k 671M ⌀ | star_events_count int64 0 40k | fork_events_count int64 0 32.4k | gha_license_id stringclasses 14
values | gha_event_created_at timestamp[us]date 2012-06-21 16:39:19 2023-09-14 21:52:42 ⌀ | gha_created_at timestamp[us]date 2008-05-25 01:21:32 2023-06-28 13:19:12 ⌀ | gha_language stringclasses 60
values | src_encoding stringclasses 24
values | language stringclasses 1
value | is_vendor bool 2
classes | is_generated bool 2
classes | length_bytes int64 7 9.18M | extension stringclasses 20
values | filename stringlengths 1 141 | content stringlengths 7 9.18M |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
e0d576ed4566aa9fb44bb6299f5e75abc0dc2b0c | f694ae8dde4e35f83913a70b85e427983823be59 | /scratch/2015-01-22-scratch.r | 53ea30d3bbe465bcd03b35b4b708158c5cabba87 | [] | no_license | wes-brooks/opticalww | b27cc1763f5d3d3be03e142c696310589798e540 | 0ed1afa4a983865fbdd65fc3667a54b60322cfdb | refs/heads/master | 2021-05-29T14:15:47.726895 | 2015-02-26T16:55:17 | 2015-02-26T16:55:17 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,236 | r | 2015-01-22-scratch.r | #find the columns corresponding to excitation-emission data
indx = grepl("f(\\d{3})\\.(\\d{3})", colnames(ss.eem)) %>% which
#set up a data frame with the excitation-emission frequencies
matches = gregexpr("\\d{3}", colnames(ss.eem)[indx])
freqs = regmatches(colnames(ss.eem)[indx], matches) %>% as.data.frame %>% t %>%... |
4c99ea6ea6f586fdc615d23f0f6641917def3f68 | e2101543bf3421c7d7b5bdc5fcd0513701f85b67 | /Assignments/2 - R Programming/Assignment2.R | e57dbbbf8f1513c6a915f801e1a8605252015456 | [] | no_license | kdivis/DataScienceSpecialization | 92f13b6d1876fadd12c0b14affaf04aa0cc574a6 | 9e30f72034684171b6cb9b1d01e144f92a2b7a1c | refs/heads/master | 2021-01-10T08:53:19.975677 | 2015-11-04T03:24:11 | 2015-11-04T03:24:11 | 45,509,483 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,471 | r | Assignment2.R | ##R Programming: Assignment 2
# -K. Divis (July 2015)
# -Created as part of Coursera Data Science Specialization
makeVector = function(x = numeric()) {
m = NULL
set = function(y) {
x <<- y
#My understanding is this: it searches the parent environment to see if x already has a value and... |
6a83734c8932358302e3a195f42ea26f9126cae3 | 1b4df2f1c29fb7bf251098ce8b4779cc9d73d7ef | /man/rotate_dot_plot_dendrogram.Rd | c2ae1d3205ddc824394d0ce4a2f3b4ab6713a3b8 | [] | no_license | Simon-Leonard/FlexDotPlot | a00c8547cac9a8cf22992cf59934e57fd0e1fbae | d6cf3048060370fefa637a21d4e1a82d974af74f | refs/heads/master | 2022-06-23T20:45:35.391673 | 2022-06-17T09:10:28 | 2022-06-17T09:10:28 | 252,197,677 | 25 | 5 | null | null | null | null | UTF-8 | R | false | true | 1,697 | rd | rotate_dot_plot_dendrogram.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rotate_dot_plot_dendrogram.R
\encoding{UTF-8}
\name{rotate_dot_plot_dendrogram}
\alias{rotate_dot_plot_dendrogram}
\title{Interactively rotate dendrograms from dot_plot outputs}
\usage{
rotate_dot_plot_dendrogram(dot_plot_output, axis_to_rota... |
c50282079a7aaeeea1b95ed8058af113bda4de9a | 7af1ca1589f16ee9e1ca03ea0de7605a25a879cd | /CreatePackage.R | 4ee34dc4eb7480528fe95281439ed419558d9549 | [] | no_license | dispersing/HexGrid | 2298919432ce48857f72e98634aa21145c0e6a30 | 5369c0c7c955c90b7ffb674ba1ba073375cfec57 | refs/heads/master | 2021-01-17T12:50:00.296049 | 2016-07-01T14:33:45 | 2016-07-01T14:33:45 | 57,258,495 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 168 | r | CreatePackage.R | library(devtools)
library(roxygen2)
pkg.dir <- "~/Dropbox/Projects/HexGrid_Package"
setwd(pkg.dir)
# create("HexGrid")
# document(paste(pkg.dir, "/HexGrid", sep = "")) |
1f545a045734f148e783662a7082c39bbccbc58d | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googlepubsubv1beta2.auto/man/PushConfig.attributes.Rd | dd15ec52bc384e05aee6d82aa4cef02b48786de7 | [
"MIT"
] | permissive | GVersteeg/autoGoogleAPI | 8b3dda19fae2f012e11b3a18a330a4d0da474921 | f4850822230ef2f5552c9a5f42e397d9ae027a18 | refs/heads/master | 2020-09-28T20:20:58.023495 | 2017-03-05T19:50:39 | 2017-03-05T19:50:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,431 | rd | PushConfig.attributes.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pubsub_objects.R
\name{PushConfig.attributes}
\alias{PushConfig.attributes}
\title{PushConfig.attributes Object}
\usage{
PushConfig.attributes()
}
\value{
PushConfig.attributes object
}
\description{
PushConfig.attributes Object
}
\details{
A... |
75ffe2913c2c543713eee42f612659369d850163 | aba55c7ed6c36fa9e3058378758471219a9268ad | /income_quintiles/income_quintiles_master_script.R | fcab90594fb550ab11221c5bf6c91a4c3492fa8e | [] | no_license | sjkiss/CES_Analysis | b69165323d992808a9d231448bcc3fe507b26aee | 4c39d30f81cbe01b20b7c72d516051fc3c6ed788 | refs/heads/master | 2023-08-18T15:18:44.229776 | 2023-08-07T22:49:06 | 2023-08-07T22:49:06 | 237,296,513 | 0 | 1 | null | 2020-05-07T19:19:08 | 2020-01-30T20:12:01 | R | UTF-8 | R | false | false | 1,983 | r | income_quintiles_master_script.R | #census income quintiles master script
source("income_quintiles/income_quintiles_1971.R")
source("income_quintiles/income_quintiles_1981.R")
source("income_quintiles/income_quintiles_1986.R")
source("income_quintiles/income_quintiles_1991.R")
source("income_quintiles/income_quintiles_1996.R")
#This is a check
quintile_... |
c68e5fbd569cc403b4ce09578bbe11ce41b0001a | f250476a3355c700099a93dada2be754c93a834d | /R-Code-Day4 - All.R | deed2919a09da1dd07dc4d28313194d9a5ebff76 | [] | no_license | balluhardik96/Data-Visualisation | 63cf4afc50d1dbf2e30bfbca5d816775eddb9e92 | 1f13c3889e3f0aa2f204a1147c70d3f64350604b | refs/heads/master | 2021-07-16T06:05:20.655893 | 2020-05-18T22:36:22 | 2020-05-18T22:36:22 | 143,678,246 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,859 | r | R-Code-Day4 - All.R | ############### Time series plot ####################################################################
# Data Set used: Economics data set
# Source of data set: R-Inbuild data set
# Problem statement: Plot the unemployment rate over the year.
library(ggplot2)
data1 = economics
chart1 = ggplot(data1, ae... |
49dfdd06bdaba1fc4e636914ce6189f5d1ad60cf | 177296a4370c7578dcad54cca9c7401c8ed4a87e | /Scripts/R_scripts/masterPlot_summStats_severalIndependentRuns.R | 40442a29dab66d5264c3c987cf5a99c165940d93 | [
"MIT"
] | permissive | diegoharta/prdm9_2020 | f6769af8fc29e55a72632c3865aa78e4764f54f3 | 44d9be7c678a7b8c0ca29ddb66a33c9c143465da | refs/heads/master | 2023-01-31T17:18:07.437443 | 2020-12-14T17:55:49 | 2020-12-14T17:55:49 | 304,371,161 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 24,454 | r | masterPlot_summStats_severalIndependentRuns.R |
#THIS FILE CREATS THE MASTER PLOT
#IT INCLUDES REAL AND EFFECTIVE MUTATION RATES, SUMMARY STATS AND RELATIVE TO THE SIZE OF ARRAY AND MUTATION TYPE
#IT GETS THE INFO FROM SEVERAL INDEPENDENT RUNS LABELLED BY _s0, _s1, etc
#THIS FILE INTENDS TO SHOW THE EVOLUTION OF SEVERAL SUMMARY STATISTICS
#This file intends to sho... |
db73bcb24b12aaab2cd5976772d7fcb4486122a0 | 05304ecee805e10390c185513306d4db02ba81b5 | /NormalCompara.R | 5a40f8ed8a7108131f1b1aaee2f51a453f9ec4f4 | [] | no_license | Cefor/eleicoes-gerais-2014-AL-PR | 5fea5187e2d4bcc292edd561f4fba1729679a76a | 6efdf7aacf083fffa08cea5d0cf1a0ccba21ad86 | refs/heads/master | 2023-02-19T22:13:50.270110 | 2023-02-10T19:34:31 | 2023-02-10T19:34:31 | 69,697,156 | 0 | 0 | null | null | null | null | ISO-8859-1 | R | false | false | 2,118 | r | NormalCompara.R |
dnormalComp <- function(media1=0, dp1=1, media2=0, dp2=1, nc=.95, rc="=")
{
########################
# Script principal
########################
# eixo x da curva normal
lim <- c(
min(c(media1+c(-4,4)*dp1, media2+c(-4,4)*dp2)),
max(c(media1+c(-4,4)*dp1, media2+c(-4,4)*dp... |
9218d0804b12d64102a7e11de10aa8dc535f732a | 807e5c79815760e935694563f247235aed81ab51 | /devdataprod-016/quizzes/quiz1/server.R | 3cb567fa67fc8dcd301993c1dbd018a752004930 | [] | no_license | gitrons62/coursera | 19233553c261e371daf740f9fb18ad945033285e | 4ff47d16e843b500f6f88a88b024a86d3093350a | refs/heads/master | 2020-04-05T23:45:54.522845 | 2015-01-10T21:34:06 | 2015-01-10T21:34:06 | 23,267,228 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 274 | r | server.R | setwd("~/R/coursera/devdataprod-016/quizzes")
shinyServer(function(input,output){
output$myname=renderText(input$name)
output$myn2 =renderText(input$n2)
output$mygender=renderText(input$gender)
output$myslide1=renderText(paste("value is:",input$slide1))
}
)
|
2e5bb84746da56d2fbeaed8289e759f38ee8f6e1 | 13eb5ef9e429d6eb25739047ccda3932a580cd07 | /knn_algorithm.R | 77e2dfe2181bc8de36e88b0805e9ed26a4ac6522 | [] | no_license | FlonairLenz/knn_r | 094f7e1863a98aed88e20b8bac72e4052c9eb2a7 | 4bcab4b79feb860a9e9da1cb79d7b90aaf87ea76 | refs/heads/master | 2020-03-13T14:05:40.834449 | 2018-04-26T16:14:14 | 2018-04-26T16:14:14 | 131,151,827 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 535 | r | knn_algorithm.R | distance <- function(x_i, x_j) {
d <- 0
for (i in 1:(length(x_i) - 1)) {
s <- x_i[i] - x_j[i]
d <- d + (s * s)
}
return(sqrt(d))
}
knn <- function(k, x_i, points) {
x_i <- as.numeric(x_i)
distances <- c()
categories <- c()
for (j in 1:nrow(points)) {
x_j <- as.numeric(points[j,])
dis... |
f65c8512171bf3dc0f97f2a1b92f956f985238e3 | eaa49ba6013f548f5db9ee9921e1c62f91451569 | /LinearModelingLectureNotes2016.R | 78a29e5a03ce8923eac24d102938ed3fe29599b0 | [] | no_license | vasishth/LM | 775d90c14105157d6f17bb7dc346ea852b293e87 | 3b5d686485a7f14360db49f16cdaf93f6f2dbf42 | refs/heads/master | 2020-12-24T05:21:49.157988 | 2020-07-22T08:37:58 | 2020-07-22T08:37:58 | 38,547,250 | 19 | 10 | null | 2016-06-07T19:30:03 | 2015-07-04T20:47:50 | R | UTF-8 | R | false | false | 32,501 | r | LinearModelingLectureNotes2016.R | ## ----include=FALSE-------------------------------------------------------
library(knitr)
# set global chunk options, put figures into folder
options(replace.assign=TRUE,show.signif.stars=FALSE)
opts_chunk$set(fig.path='figures/figure-', fig.align='center', fig.show='hold')
options(replace.assign=TRUE,width=75)
opts_c... |
e693220681d6be057bcd9fb500f6a20eaab2ba0b | eb609bed8415c07c74967efb85c9ab063d6754a5 | /R/toJSON.AAAgeneric.R | b9dca46a784cb3e8a7fbb1e1dd5db019aae845f8 | [] | no_license | cran/opencpu.encode | 44015acd51f7fd1fb41abdef96eaf193883a8e49 | 922e50864ece2c4a778af2603a329b5bab1958b0 | refs/heads/master | 2016-09-06T10:53:08.837639 | 2011-08-05T00:00:00 | 2011-08-05T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,408 | r | toJSON.AAAgeneric.R | # TODO: Add comment
#
# Author: jeroen
###############################################################################
#This file is called AAA so that it will be run first.
#' Serialize an R object to JSON.
#'
#' This is a slightly modified version of the asJSON function in RJSONIO. This function is mostly for inte... |
50d590267b4080dfb4e58a9a78a5975821b668ba | bea761df375b43eed5edaf219cf7f3f5d2cbaba3 | /man/ovl4.Rd | 1f8270fedc36e179e6f109dbf1e4424be5998465 | [] | no_license | cran/activity | e33f70b7f26e62b4e16dbac3677db0558da046bc | 8e86e73148d0285a89962441d267ac840cd9505b | refs/heads/master | 2023-03-23T14:32:57.830107 | 2023-03-02T16:20:05 | 2023-03-02T16:20:05 | 24,599,140 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 937 | rd | ovl4.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/activity_code.r
\name{ovl4}
\alias{ovl4}
\title{Index of overlap between circular distributions.}
\usage{
ovl4(fit1, fit2)
}
\arguments{
\item{fit1, fit2}{Fitted activity models of class actmod created using function fitact.}
}
\va... |
d3f1eb723c8f88758cf7b96827929f9433fb50f9 | bdc8a312721efe4f4d41fed1a6b5cfb03f04f1a8 | /Diatom_counts/Basic_clusters.R | 79db45a4b011d90eb38bf4355dd7a01b7d8e1c24 | [] | no_license | sergemayombo/Diatoms | 1a09063e72787855820305bbc5136ad4d8662e81 | 03c7d37f3616261f2718af9c8f5cb9626fbb7f5a | refs/heads/master | 2020-04-22T20:52:32.113273 | 2019-05-27T12:55:26 | 2019-05-27T12:55:26 | 170,654,883 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,179 | r | Basic_clusters.R | # Epiphytic diatoms associated with the south African kelp
# Diatom data exploration, analysis and presentation.
# Mayombo Ntambwe
# 11th Febraury 2018
library(tidyverse)
library(vegan)
library(cluster)
library(ggplot2)
library(ggdendro)
library(tcltk)
library(BiodiversityR)
library(readr)
# read in the data
cou... |
f45e2b624387fe63c888aca90ec0ca89a4e990c0 | dab05df8a6ddf8947638c2bc2c3b5946d13771e2 | /man/Web2.Rd | 0277a153077faae9e05789bb40897ecc478286fe | [
"MIT"
] | permissive | tpemartin/econR | 2011047b7ef100b27fffd99148a7698ce7f99930 | 5df4fd5bf61b417b9860b3efc7ff20339e694fe4 | refs/heads/master | 2023-09-05T03:34:20.354596 | 2021-11-23T12:22:42 | 2021-11-23T12:22:42 | 335,521,237 | 0 | 4 | null | 2021-03-17T07:18:16 | 2021-02-03T05:48:23 | HTML | UTF-8 | R | false | true | 229 | rd | Web2.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/webapp2.R
\name{Web2}
\alias{Web2}
\title{web instance generator}
\usage{
Web2()
}
\value{
}
\description{
web instance generator
}
\examples{
None
}
|
4848891d5bc8dbfd9a136885f79a1d9f59dd1b84 | 051fd5c23ce8ebbedc506ac9028d08b3d3a45e25 | /scripts/OC_2011.R | 338d17b6afbd9b43e08d3b540ce7dfd97a8a2a16 | [] | no_license | TheresaStoll/Practical_session_own_data | cc6d13b2964045bc716b3f24e968afdd87bd58d2 | 58730c5e4a99a25b55328efd0b193334226ec26c | refs/heads/master | 2020-08-09T08:29:23.546214 | 2019-10-10T05:38:42 | 2019-10-10T05:38:42 | 214,048,531 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,432 | r | OC_2011.R | library(tidyverse)
#to check working directory
getwd()
#to set the working directory
#se the Tools | Change Working Dir... menu (Session | Set Working Directory on a mac).
#This will also change directory location of the Files pane.
#https://support.rstudio.com/hc/en-us/articles/200711843-Working-Directories-and-Work... |
310ebf6e6769f02eed4a0e1b7d19324a1ca41f9f | 5b7a0942ce5cbeaed035098223207b446704fb66 | /man/lsGetSurveyProperties.Rd | f47aa8c89b15ca650d7b09f396ac4f8dd6461f39 | [
"MIT"
] | permissive | k127/LimeRick | 4f3bcc8c2204c5c67968d0822b558c29bb5392aa | a4d634981f5de5afa5b5e3bee72cf6acd284c92a | refs/heads/master | 2023-04-11T21:56:54.854494 | 2020-06-19T18:36:05 | 2020-06-19T18:36:05 | 271,702,292 | 0 | 1 | null | 2020-06-12T03:45:14 | 2020-06-12T03:45:14 | null | UTF-8 | R | false | true | 1,321 | rd | lsGetSurveyProperties.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/lsGetSurveyProperties.R
\name{lsGetSurveyProperties}
\alias{lsGetSurveyProperties}
\title{Get survey properties}
\usage{
lsGetSurveyProperties(
surveyID,
properties = NULL,
lsAPIurl = getOption("lsAPIurl"),
sessionKey = NULL
)
}
\argu... |
16dfa7a95b262daf083dcef169d91a8ea2cc8563 | 961523bd8d12ac6e6f5fa5a6c85bda7261d6035f | /computational_statistics/hw4.R | 2a7e8a8cb3d0ef4b14a8dbdd20fe9576d0513fbd | [] | no_license | keepproceeding/Study_R | d7a58bd230a1c05ea0dd6dd00551395012f186a1 | 06397f5b2aee2041e7228f2baeb40574b09de782 | refs/heads/master | 2023-03-02T02:35:36.589620 | 2021-02-14T14:20:51 | 2021-02-14T14:20:51 | 334,445,440 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 919 | r | hw4.R | #1
random_uni<-function(seed){
x<<-c()
for(i in 1:100){
seed <- (16807*seed)%%2147483647
x[i]<<-seed/2147483647
}
x
}
random_uni(2020)
ks.test(random_uni(2020),runif(100))
install.packages("snpar")
library('snpar')
runs.test(random_uni(2020))
#2
length(which(rbinom(1000,6,0.2)>=1))/1000
mean(rbinom(10... |
ce08f8d8c406686c369edc12d9fd7967aa0d6fdd | 753e3ba2b9c0cf41ed6fc6fb1c6d583af7b017ed | /service/paws.ses/man/create_configuration_set.Rd | 96ccb834310eafe88946fcfc3ec20132941a6096 | [
"Apache-2.0"
] | permissive | CR-Mercado/paws | 9b3902370f752fe84d818c1cda9f4344d9e06a48 | cabc7c3ab02a7a75fe1ac91f6fa256ce13d14983 | refs/heads/master | 2020-04-24T06:52:44.839393 | 2019-02-17T18:18:20 | 2019-02-17T18:18:20 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 856 | rd | create_configuration_set.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/paws.ses_operations.R
\name{create_configuration_set}
\alias{create_configuration_set}
\title{Creates a configuration set}
\usage{
create_configuration_set(ConfigurationSet)
}
\arguments{
\item{ConfigurationSet}{[required] A data structure th... |
07815479c6b0d82177d1945f755ea5007d81c63b | e6fe0284ac73cb98b1ffd4cd4831bd65d43bd546 | /PredictiveTextAnalyticsToCourtRoom.R | 8e53126e02031237d8fc9919ddc45cafedd6f4af | [] | no_license | zahidmak/dataAnalysis | 08df3707647e6aa08721d0827f288e980028f90d | 88814f11ba41f07275be26d1330c0b86219a5bc3 | refs/heads/master | 2021-04-30T22:37:07.599997 | 2016-10-17T02:25:25 | 2016-10-17T02:25:25 | 71,092,579 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,192 | r | PredictiveTextAnalyticsToCourtRoom.R | rm(list=ls())
emails=read.csv("C:/Users/Zahid/Downloads/energy_bids.csv", stringsAsFactors=FALSE)
str(emails)
emails$email[1]
emails$responsive[1]
emails$email[2]
emails$responsive[2]
table(emails$responsive)
library(tm)
corpus=Corpus(VectorSource(emails$email))
corpus[[1]]
corpus=tm_map(corpus, tolower)
corpus=tm_map(... |
66b4be1d3df20bbbda171144273e0c92cdff82a5 | 4664b04b2bfc82ed82e300822f61229932cbfd32 | /tools/phylotime_tools.R | fb68cf62e4e1a67f2f14b7ca790120b40816fb49 | [] | no_license | DomBennett/Project-EPI | d71bac553c5c988b5f7798f062faa329dafd62ac | f464dc1c53643ee101063e4d9c4cb7b06f0a4b83 | refs/heads/master | 2021-05-01T10:40:55.384250 | 2018-04-16T09:57:33 | 2018-04-16T09:57:33 | 14,775,462 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,331 | r | phylotime_tools.R | assgnWMean <- function(val, nm) {
# assign a value to node_obj multiple times
# if value already present, work out mean
if(is.null(node_obj[[txid]][[nm]])) {
node_obj[[txid]][[nm]] <- val
} else {
# otherwise get mean
node_obj[[txid]][[nm]] <-
(node_obj[[txid]][[nm]] + val)/2
}
}
getTree <-... |
a1fd5a5a354bdea295d122cd5234411b02b8ddb4 | ffc352b6c70d8a9ee7712cede9afeba5a028fc06 | /scripty.R | 02e8cbe13439126b9e98e000d2690db340589fb1 | [] | no_license | ssarapark/polity-genderdiscrimination | 11bbed90166c47287a743eca16fd817e6d36bffb | f1fc1b385d0eca81396e43275a1c9eb61eec680e | refs/heads/main | 2023-02-06T14:03:50.636798 | 2020-12-13T02:28:49 | 2020-12-13T02:28:49 | 320,966,006 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,315 | r | scripty.R | oecd <- read_csv("finalproject/oecd_data.csv",
col_types = cols(LOCATION = col_character(),
INDICATOR = col_character(),
SUBJECT = col_character(),
MEASURE = col_character(),
... |
925f88e5ee9b24804412d8760fcee50f751e2bbf | fe254ef6be0bd316d41b6796ef28f1c9e1d5551e | /R/aDist.R | e691c5571da84b8a779465c279da76aa2592a5d0 | [] | no_license | matthias-da/robCompositions | 89b26d1242b5370d78ceb5b99f3792f0b406289f | a8da6576a50b5bac4446310d7b0e7c109307ddd8 | refs/heads/master | 2023-09-02T15:49:40.315508 | 2023-08-23T12:54:36 | 2023-08-23T12:54:36 | 14,552,562 | 8 | 6 | null | 2019-12-12T15:20:57 | 2013-11-20T09:44:25 | C++ | UTF-8 | R | false | false | 4,076 | r | aDist.R | #' Aitchison distance
#'
#' Computes the Aitchison distance between two observations, between two data
#' sets or within observations of one data set.
#'
#' This distance measure accounts for the relative scale property of
#' compositional data. It measures the distance between two compositions if
#' \code{x} and \co... |
ce546cc37c5941301f8bbe7dd40db27f2ff83235 | 829ddd5de43968ccd4da02cdce17bf5a5a343a57 | /src/a/phytometer/plantcounts.R | 34ff20eff5311e05d0eede6b1630ffeaeda80b37 | [] | no_license | martinzbinden/droughtlegacy_old | cd99f453f804474423f109a7d666f106d8ea6090 | 97154c99f83adde0f94948867d51ce8e3c3e2b23 | refs/heads/master | 2021-01-19T22:33:34.521179 | 2014-11-20T22:07:36 | 2014-11-20T22:07:36 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 771 | r | plantcounts.R | ##example dataset
## 11 means more than 10 -> means may not be accurate!
df <- data.frame(
place=c(rep("ZOL",4), rep("ZOL",4), rep("THU",6)),
plot=c(rep(1,4), rep(2,2), rep(1,6) ),
subplot=c(rep(2,4), rep(3,2), rep(2,6)),
species=c(rep("linum",6), rep("linum",4), rep("silene",2)),
rep=c(1:4,1:2, 1:4, 1:2)... |
922617cbbeb98bc20463a84ad9b9e0910a8212ac | 8ce288d090c16bfc69402e69ee2c6a3cd540fb12 | /inst/unitTests/test_dim.R | 501e9d2b2a779c14c97353e2fe4169f30180521e | [] | no_license | MattNapsAlot/bigDataFrame | df57bb9dc71ea6f3b2e21bb4c50f6a04d17271b4 | 68ef32d618559aa5a615601b85c2101b0f5c5137 | refs/heads/master | 2020-05-16T22:43:34.991909 | 2012-01-03T04:17:29 | 2012-01-03T04:17:29 | 3,043,211 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 560 | r | test_dim.R | .setUp <-
function()
{
}
.tearDown <-
function()
{
}
unitTestSetDims <-
function()
{
df <- new(Class="BigDataFrame", hdfFile=tempfile(fileext=".h5"))
checkTrue(all(dim(df) == 0))
checkEquals(length(dim(df)), 2)
dim(df) <- c(0,0,0)
checkTrue(all(dim(df) == c(0,0)))
dim(df) <- c(1,1)
checkTrue(all(dim(df... |
c08c3c63f8fc25267ec3700febf6d589f39d6365 | b6f822b70438a41ff973fb0bacad20321805606a | /figures/Encelia_maps.R | d7b5a012ec157e43ddbc5a0fde9470d141907a0f | [] | no_license | singhal/encelia_phylogeny | 213a89e178ce754bf2264a5097fa67aec96c5b33 | 962ffe685835c6dc95399f763a6681ec502a1f85 | refs/heads/main | 2023-02-11T03:17:03.128569 | 2021-01-14T00:06:41 | 2021-01-14T00:06:41 | 329,459,390 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 4,199 | r | Encelia_maps.R | library(ggplot2)
library(cowplot)
library(rnaturalearth)
library("rnaturalearthdata")
theme_set(theme_cowplot())
library(readr)
library(dplyr)
library(tidyr)
library(RColorBrewer)
library(ggtree)
world <- ne_countries(scale = "small", returnclass = "sf")
# sampled points
spoints = read_csv("~/Dropbox/Encelia/analysis... |
462bb09bd6998a1ab68159e5e97db809a7b78360 | 13fcf4ad90ebdaf4cb04cfd0c3453e57cd32d851 | /man/getDoTerm.Rd | 780d5558044f496360e195417c358397e24c5f38 | [] | no_license | cran/DOSim | eaf99f78e9dee69d12811ff5cd8726d957fa3aaf | a8d198f75aa4e90910612c42c4092f3bb1763819 | refs/heads/master | 2021-01-19T07:54:29.405777 | 2012-02-12T00:00:00 | 2012-02-12T00:00:00 | 17,717,409 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 845 | rd | getDoTerm.Rd | \name{getDoTerm}
\alias{getDoTerm}
\title{
Get DO term's name
}
\description{
Returns the list of DO term's name associated to each DO ID.
}
\usage{
getDoTerm(dolist)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
\item{dolist}{
character vector of DO IDs
}
}
\value{
List with entry names f... |
0cd58dde90ad759ed96357dc08046e61cd88ba8d | 17207b55047c6a7141fae2c6c0a3326a114206be | /man/Canonicalization-class.Rd | 55f4cbae7c8716724084a75351b9b54efec54325 | [
"Apache-2.0"
] | permissive | bedantaguru/CVXR | eab395c4262b8404c11d8ba6196d0368a0b1887f | b1b9b0cb98ab909bc3781e96d3720dde37706dbd | refs/heads/master | 2020-11-30T00:04:26.138136 | 2019-12-11T21:31:28 | 2019-12-11T21:31:28 | 230,246,740 | 1 | 0 | null | 2019-12-26T10:43:28 | 2019-12-26T10:43:27 | null | UTF-8 | R | false | true | 1,620 | rd | Canonicalization-class.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/reductions.R
\docType{class}
\name{Canonicalization-class}
\alias{Canonicalization-class}
\alias{.Canonicalization}
\alias{perform,Canonicalization,Problem-method}
\alias{invert,Canonicalization,Solution,InverseData-method}
\alias{canonicaliz... |
7d2e0696382f169ca77ece3d7edf92f5bc0f3858 | ec2c6eb45f2155d66f4daa62cb9cf60211b769d7 | /factors.R | d3bff1a4aef2825c2b3e9550f74fd1a46d67d32c | [] | no_license | mindcrime/LearningR | dedf431d39d4622e6d601b395bbae9147cab1e41 | 04de699585927edc73797bf78a4b5bf18ce45a7e | refs/heads/master | 2020-05-09T18:10:34.277064 | 2015-12-25T12:14:59 | 2015-12-25T12:14:59 | 40,801,362 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,263 | r | factors.R | # Working with factors
# Filename: factors.R
# Author: prhodes
###############################################################################
# factors are for storing "categorical" data (ex, "male" and "female" or "small", "medium", "large", etc.)
# if you create a data frame with a column of text data, R will assu... |
303de41ae2d97bd805f7244e3668ecbc4e5f788f | ed69b9b15821c94608e172cd7113e9a73d51c1c3 | /FLVoters/FLVoters.R | 70f0944497595814648e6591ab29ba4faacb5780 | [] | no_license | anhnguyendepocen/Econ_5043 | 410e85a5fae43d2a653052204273fb5e3808a43b | 592451ca6c2fef2cd22dc905c8acaad51d896860 | refs/heads/master | 2021-09-14T09:01:58.774073 | 2018-05-10T21:45:12 | 2018-05-10T21:45:12 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,160 | r | FLVoters.R | '''
Note that there were some parts that were buggy
'''
#Load Data
#census data
cnames<-read.csv("cnames.csv")
head(cnames)
#Florida census data
FLCensus<-read.csv("FLCensusDem.csv")
head(FLCensus)
FLVoters<-read.csv("FLVoters.csv")
head(FLVoters)
FLCensusVTD<-read.csv("FLCensusVTD.csv")
head(FLCensusVTD)
#1) sp... |
1635f8ccfe3cce6da0025e405e333f19a9614eb2 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/suncalc/examples/getMoonTimes.Rd.R | 7f421f9ee6b9fcf16ddd28af03a4f5aa9d70d9f8 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 599 | r | getMoonTimes.Rd.R | library(suncalc)
### Name: getMoonTimes
### Title: Get Moon times
### Aliases: getMoonTimes
### ** Examples
# one date
getMoonTimes(date = Sys.Date(), lat = 47.21, lon = -1.557, tz = "CET")
# multiple date + subset
getMoonTimes(date = seq.Date(Sys.Date()-9, Sys.Date(), by = 1),
keep = c("rise", "set", "alwaysU... |
64834ad393bb9a3e5a252138e776f5b179b1e7ee | 567ae9b443f9e3599b8f19d8616ad75a924eecef | /HW1.R | 9a425d823afb7db7cf4bf823daa46f978682daa0 | [] | no_license | sdmurff/STATS-240P | 40c811eeebd60f728b37c77ddced2dc33f5478c5 | f547281b4843aec8192b2890588af8245cc7d770 | refs/heads/master | 2022-08-10T23:14:09.419415 | 2022-07-29T03:49:13 | 2022-07-29T03:49:13 | 43,308,225 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,755 | r | HW1.R | ## @knitr HW1point6
#### Exercise 1.6 ####
X <- read.table('http://web.stanford.edu/~xing/statfinbook/_BookData/Chap06/w_logret_3stocks.txt', header=T)
# Convert Date column from a factor to an R date
X[,1]<-as.Date(X[,1],"%m/%d/%Y")
## @knitr a1_6_1
#### 1.6 (a) ####
# Plot Pfizer returns and add lines to highlight b... |
4d2bc8a39b5fc9d17723871c8fb16a5c244c2276 | 52ccefaad3cbdd746065b0501962516207646140 | /Chpp 6.R | 96b375fc35c5e9543829ddd9870e64c45009cf80 | [] | no_license | Pushpit07/R--Programming--Cotton | 030274e563db60e605ffa36ff0b9e2b112b0f7c3 | 4828e806533d30fffa6bdab160154264b95c7357 | refs/heads/master | 2023-04-14T22:10:09.622979 | 2021-04-24T04:30:31 | 2021-04-24T04:30:31 | 336,554,121 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,874 | r | Chpp 6.R | an_environment <- new.env()
an_environment[["pythag"]] <- c(12, 15, 20, 21)
an_environment$root <- polyroot(c(6, -5, 1))
assign(
"moonday",
weekdays(as.Date("1969/07/20")),
an_environment
)
an_environment[["pythag"]]
an_environment$root
ls(envir = an_environment)
ls.str(envir = an_environment)
exists("pythag... |
a9bc3ff07a51e0d2cdbf4e6f2b423e6fa5235909 | c88a451c5dd8dab775fc61e2c007bdcdde33149e | /ui.R | 3d3921d5bc8e3ab39516818237c0c4c2996caf3d | [] | no_license | davidmanero/Shiny-Spanish-Books | 0682fdc6525493adad187543b19fc9cf94fdfb3b | ea0bdbd8e77faacd058ab55615bc536740d74b73 | refs/heads/master | 2021-01-10T12:51:14.390477 | 2015-09-27T18:22:25 | 2015-09-27T18:22:25 | 43,258,079 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,854 | r | ui.R | library(shiny)
shinyUI(
navbarPage("Best Spanish Books Word Cloud",
tabPanel("Detail",
h2("Spanish Best Books Word Cloud"),
hr(),
h3("Description"),
helpText("This is an application that gives a Word Cloud Analysis o... |
001fc26e340aac9f65976936f34f13e10822178c | 0f43b7df4006ca85de76f5209b85aa39c649150f | /R/export_csv.R | cbd33d857cb8a09c603b6d354871061e80367bb4 | [] | no_license | sybrendeuzeman/WIOD_package | 29c66e8b17415236421c534c309c1f712cf860ac | edcb5485bd4d49b9a6310d7dfc172f1d8864366c | refs/heads/master | 2020-07-02T04:44:56.131660 | 2020-01-23T18:22:31 | 2020-01-23T18:22:31 | 201,419,749 | 1 | 0 | null | 2020-01-23T18:22:32 | 2019-08-09T07:54:13 | R | UTF-8 | R | false | false | 2,051 | r | export_csv.R | # Function to extract measures from iots into a .csv file
# Created by: Sybren Deuzeman
# Maintained by: GGDC
# First version May 2019
# Current version: 11 June 2019
#' @import tcltk
#' @title Make a CSV file from measures in IOTs
#' @description Function to extract measures from IOTs into a CSV file
#' @param mea... |
505531c39d735fc177c75f046b7ecf3889016315 | fde3f786a46570dcdc728538f756d6e3f30045eb | /R/QM12-02D/02-anaResults.R | eb2c33bc49554f93a647c11f15764f3fd820aa0d | [] | no_license | jrminter/snippets | 3fcb155721d3fd79be994c9d0b070859447060d7 | bb3daaad5c198404fef6eaa17b3c8eb8f91a00ed | refs/heads/master | 2021-01-13T14:20:51.451786 | 2017-04-29T05:26:11 | 2017-04-29T05:26:11 | 16,347,209 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 7,132 | r | 02-anaResults.R | # 02-anaResults.R
rm(list=ls())
library(xtable)
str.id <- 'FY26H-09-01'
# str.mode <- 'raw'
str.mode <- 'ellipse'
str.wd <- "~/work/qm12-02d-02/R/R/"
i.digits <- 4
# png dimentions
png.w=800
png.h=600
# should not need to change below here...
# set up functions
# compute the standard error
stderr <- function(x) sq... |
7b1f51cc4f4763c08b9261b04edf76569a04c340 | b9c5fe4799dfd8b0e73f604158f4e7071974fa85 | /ogbox.r | e5b08ade46b80eedd72239d31c3face2571416c6 | [] | no_license | oganm/Rotation-3 | 50b12ea35d3ee611f11d227d96a83714e62c49f8 | f0fecc0c64efe95a1a732c2ca73a3cbbb69cf114 | refs/heads/master | 2021-01-13T02:36:22.277925 | 2014-11-07T00:13:36 | 2014-11-07T00:13:36 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,018 | r | ogbox.r | gsubMult = function(patterns, replacements, x,
ignore.case = FALSE, perl = FALSE, fixed = FALSE, useBytes = FALSE) {
for (i in 1:length(patterns)){
x = gsub(patterns[i],replacements[i],x,
ignore.case, perl, fixed, useBytes)
}
return(x)
}
#paste to directory... |
e93bc25352b43e4d6646e105f2b0348d64f93bd1 | ed400c77295c4e95a26576a5dd8aac436aa0e2f9 | /code/library/generateVarpepSAAVs/generateVarpepSAAVs.R | df8d0bfc5f31fe5aa02b07bb04856f0778ff71cb | [
"Apache-2.0"
] | permissive | KnowledgeCaptureAndDiscovery/wings-genomics | 960819a6d96108a4b2e145e13fbe92ac3f382393 | 0e6387eecd0ab7af24290d3441785a02ef19adf9 | refs/heads/main | 2023-04-09T23:30:08.322715 | 2022-06-30T18:16:59 | 2022-06-30T18:16:59 | 350,090,124 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,087 | r | generateVarpepSAAVs.R | # Format and generate variant peptide and SAAV data
formatVarpepAndSAAVs <- function(var.pep.df, saav.colname,
pro.colname, var.colname,
dbsnp.colname, pep.format.colname,
pep.seq.colname, to.remove.colnames,
group.by.cols) {
var.pep.df[,saav.colname] <- do.call(paste, c(var.pep.df[c(pr... |
912877987c9d3d3aa38bbc7718b496deb4159f58 | 0c4ede35db089f24d1c5e26c2a92d485debe681d | /man/check_files.Rd | d1d2f0f33a8e57f5c763b27e9b544eb4c4b9fb89 | [] | no_license | cran/assertable | 9b1c3032d47dcb19be1249198302d54f71eb8c2f | 06f179e4dc06b55d4f2612782f098a580dfd7bc2 | refs/heads/master | 2021-08-07T15:46:52.715033 | 2021-01-27T05:30:15 | 2021-01-27T05:30:15 | 78,937,106 | 0 | 1 | null | 2020-04-21T17:55:27 | 2017-01-14T11:47:59 | R | UTF-8 | R | false | true | 2,097 | rd | check_files.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/check_files.R
\name{check_files}
\alias{check_files}
\title{Check for the existence of a vector of files, optionally repeated for a set amount of time.}
\usage{
check_files(filenames, folder = "", warn_only = FALSE,
continual = FALSE... |
6327c9318b65f9d7b3dc12624a95f59f0a0dd621 | 73fc537bb4ca79f15edebcbfef0c90878666380c | /man/dateCheck.Rd | 78f5e783694cf1779c943561588a4e47bb90933b | [] | no_license | cran/ensembleBMA | b3012f476e3c7e44580edb9fb23e06bec7fce12c | 2bbb7ed69a64dd97b55a40d832b19fbc77e89b10 | refs/heads/master | 2022-09-16T14:20:24.345306 | 2022-09-02T06:20:05 | 2022-09-02T06:20:05 | 17,695,812 | 2 | 3 | null | null | null | null | UTF-8 | R | false | false | 943 | rd | dateCheck.Rd | \name{dateCheck}
\alias{dateCheck}
\alias{getHH}
\title{
Checks date format.
}
\description{
Checks that the character form of a vector of dates conforms to
YYYYMMDDHH or YYYYMMDD.
}
\usage{
dateCheck(YYYYMMDDHH)
}
\arguments{
\item{YYYYMMDDHH}{
A character vector (or its factor equivalent) of dates whi... |
25e4a994fdec9c19cfc82130cdfec5e7b0cb29fc | 07f9ba53c35091bb55094a0244a2701056bd3323 | /man/player_scores.Rd | 4344948cf993fcfe15623bc355cb05f7dd0220d5 | [] | no_license | MrDAndersen/mfl2R | cd1b9e4ed479c4cc7595a4cb5f8a5fd01deed4e7 | fa3496dbffaf7a55e2b990709e75a9122f8ae5a9 | refs/heads/master | 2022-12-12T15:53:21.890433 | 2022-11-30T15:08:19 | 2022-11-30T15:08:19 | 249,209,957 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 333 | rd | player_scores.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/league.R
\name{player_scores}
\alias{player_scores}
\title{Player scores for active league}
\usage{
player_scores(
week = NULL,
season = NULL,
player_id = NULL,
position = NULL,
status = NULL,
rules = NULL,
count = NULL
)
}
\des... |
12bba0104306d6a9b26fb36efd02dac42efce2ce | 1f33a90808ba87ebfabaeea8ce74f52af2a6a6f9 | /example-points.R | 9ee83dee8d80362ea5bf54c1a52f49fa50abf4c8 | [] | no_license | kelvingl/osm-examples | 771dc811067895f750b011d90e453cda5d4bb4b7 | bc3c62ceb58bc8b9cf8652d2f4331a9e378801aa | refs/heads/master | 2021-05-15T09:22:18.610099 | 2017-10-30T10:03:01 | 2017-10-30T10:03:01 | 108,037,541 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 815 | r | example-points.R | # Instala pacote - CUIDADO, necessita dos pacotes gdal-bin e libgdal-dev no linux
install.packages(c("OpenStreetMap"))
# Carrega pacote
library(OpenStreetMap)
# Gera um mapa mundial simples
map <- openmap(
upperLeft = c(85.0, -180.0),
lowerRight = c(-85.0, 180.0),
type = "osm"
)
# Cria projeção do mapa, para... |
df5bd6b5d1e9f3e0c2e9299e9cb2073134e18f0a | 8bb44eb98bfd9163de85e190ab809998498ef5b3 | /forecasting/forecasting_class_examples/7SARIMA(1).R | 79e85e156d4720e8775fb0a7733e7c8705ab0563 | [] | no_license | Tom-a-Hawk/VCU_DAPT2018 | c63e416d7d2ada00f6d4822828e257560fa4ef95 | 0c8972037ed06c4d88c738eb488cfb72a1b69919 | refs/heads/master | 2021-07-24T20:57:13.676108 | 2017-11-02T21:01:10 | 2017-11-02T21:01:10 | 108,593,161 | 0 | 0 | null | 2017-11-02T20:57:47 | 2017-10-27T20:34:22 | Python | UTF-8 | R | false | false | 1,147 | r | 7SARIMA(1).R | library("forecast")
Amtrak.data <- read.csv("C:\\Users\\jrmerric\\Dropbox\\Teaching\\Exec Ed\\Decision Analytics\\Forecasting\\2017\\Amtrak data.csv")
ridership.ts <- ts(Amtrak.data$Ridership, start = c(1991,1), end = c(2004, 3), freq = 12)
plot(ridership.ts)
nValid <- 36
nTrain <- length(ridership.ts) - n... |
690f569abb26130a65c50f65e966e7eb9b01b17f | e7b6bc6856ce7e42dceae1de7da92dbc9667dadc | /man/SeqDataFrame-class.Rd | 31a38c87726c59e16c41a023f1685b85b4944f18 | [] | no_license | cran/distrSim | 78ec9de63d081d6bcba03289582e3607b94cf05b | 6ca1b59990b53198b52d5e42f904c817842f7200 | refs/heads/master | 2022-11-20T09:17:24.943963 | 2022-11-12T21:10:02 | 2022-11-12T21:10:02 | 17,695,555 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,454 | rd | SeqDataFrame-class.Rd | \name{SeqDataFrames-class}
\docType{class}
\alias{SeqDataFrames-class}
\alias{SeqDataFrames}
\alias{seqDataFrames}
\alias{obsdimnames}
\alias{obsdimnames-method}
\alias{obsdimnames,SeqDataFrames-method}
\alias{obsdimnames<-,SeqDataFrames-method}
\alias{names,SeqDataFrames-method}
\alias{names<-,SeqDataFrames-... |
2bfd16e564a35821a666dc2f2cef3189f9b777be | 97ba3a8e81ddeca9a60f1b042e0c6db0e612f84e | /R/OutOfSampleTesting.R | 335dc4c395d99c8866b443735ce19fbc011ea54a | [] | no_license | avnit/Project | d3bfa9d45b9c44ad89bee2dc77ba3bb8dc21e153 | 6bd24921178dbd0a1b6ac0281c78a2f3f6f7f097 | refs/heads/master | 2020-04-11T10:44:34.628821 | 2016-02-20T14:58:37 | 2016-02-20T14:58:38 | 51,187,007 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 563 | r | OutOfSampleTesting.R | #Parameters
initDate = "2001-01-01"
# In sample
from="2012-01-01"
to = "2013-01-01"
#decisions
BuyChange<-0.1
sellChange<--0.2
buyRSi<-70
sellRsi<-30
BuyCci<-60
SellCci<-20
buyBbanbs<-0.7
sellBbands<-0.3
thresholdVol <- 0
initEq = 50000
# initialize the portfolio and download data
source('~/Project/R/initialize.R')
... |
4627438308308972b9ff63afc45be023f584caba | e3bb40da9819ee080f19b7cb710edd029f18baa3 | /plot3.R | 74b365fe5b36a4fd31da792b8aa04e5fde8d09fb | [] | no_license | diegocaggiano/Exploratory_Data_Analysis | 8a97d30a834bf45f1df49c3b79f1030e65d32608 | dab529c0115eac60fe35eca7f75af6b76d0943a2 | refs/heads/master | 2020-03-31T07:06:00.080271 | 2018-10-24T01:00:05 | 2018-10-24T01:00:05 | 152,008,061 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,015 | r | plot3.R | #Load libraries
library(readr)
library(dplyr)
library(chron)
library(lubridate)
#Load dataset from file
ds<- read.csv2(file="household_power_consumption.txt",header = TRUE, sep=";", na.strings=c("?"), stringsAsFactors = FALSE)
#Create dataset with new field DateandTime
hhpc_total<- mutate(ds, DateandTime = as.POSIXct... |
72e52368b3ae9e3937259f379cd98fb5052b410b | 56d937e8df4e5a6bf6b8f45acd68a2efdcf9d1e1 | /main.R | 561994514cea98bbdc3c2e9157732e9ece521179 | [] | no_license | efcaguab/pollen-competition | d46b970979db61dfce1e807f9ee0b59671a178b8 | bb0db4eaa5010d126df111c3fa877a3a5f1fcd29 | refs/heads/master | 2022-04-19T14:47:43.818651 | 2020-03-28T05:58:44 | 2020-03-28T05:58:44 | 83,257,340 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,715 | r | main.R | # Prepare workspace -------------------------------------------------------
pkgconfig::set_config("drake::strings_in_dots" = "literals")
library(magrittr)
library(foreach)
library(drake)
# load functions
f <- lapply(list.files("code", full.names = T), source)
n_replicates <- 99
transformation <- function(x) log(x +... |
dd19a06be6ee78d09fc756075d280989fcc1ac42 | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googledataflowv1b3.auto/man/SeqMapTask.userFn.Rd | 80ebce96dcfa77319d9bf65b8763f1b10bb55285 | [
"MIT"
] | permissive | GVersteeg/autoGoogleAPI | 8b3dda19fae2f012e11b3a18a330a4d0da474921 | f4850822230ef2f5552c9a5f42e397d9ae027a18 | refs/heads/master | 2020-09-28T20:20:58.023495 | 2017-03-05T19:50:39 | 2017-03-05T19:50:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 461 | rd | SeqMapTask.userFn.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dataflow_objects.R
\name{SeqMapTask.userFn}
\alias{SeqMapTask.userFn}
\title{SeqMapTask.userFn Object}
\usage{
SeqMapTask.userFn()
}
\value{
SeqMapTask.userFn object
}
\description{
SeqMapTask.userFn Object
}
\details{
Autogenerated via \code... |
dde10120c43722c6efe914376cc3b1c2da65be34 | 6ff4577459aec8c589bab40625301f7eefc82e73 | /R/lmWrapper-glmer.R | 720e408e4fdaf9e4c3dd790ef2b71c9405de655c | [] | no_license | lagzxadr/MAST | f1cb34efdb42d2c4eb2b6383eff02193a8e69409 | a079646898349315a676b56b6a77ca7dd17ec449 | refs/heads/master | 2021-04-27T16:27:16.229846 | 2017-12-22T16:19:32 | 2017-12-22T16:19:32 | 122,302,743 | 1 | 0 | null | 2018-02-21T06:59:29 | 2018-02-21T06:59:29 | null | UTF-8 | R | false | false | 12,892 | r | lmWrapper-glmer.R | ## This is a horrible hack, and should be rewritten to use the lmer internals.
## But in the meantime: we make the fixed effects model matrix, then call the formula method for lmer/glmer
## This is to allow us to do arbitrary LRT tests and add/drop columns of the design
## Details:
## Invariants:
## 1. model.matrix co... |
cc6203a079fc4cde41e884f4b2424e781d3245f0 | c61ab862399d908d556ee7af346ab8fbbd9777b4 | /man/plot_hierarchy_shape.Rd | 6bf8b1614a41f24f91df410c25cb54ba7d64d0e5 | [] | no_license | cran/aniDom | 539593cb59e77747a5da8cf15673049b63d862c1 | cb39e082602cb1e640a0a8b39057664500adcc7a | refs/heads/master | 2021-07-15T10:27:05.038337 | 2021-03-06T22:50:36 | 2021-03-06T22:50:36 | 81,476,233 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,125 | rd | plot_hierarchy_shape.Rd | \name{plot_hierarchy_shape}
\alias{plot_hierarchy_shape}
\title{
Plots the shape of a dominance hierarchy from empirical data
}
\description{
This function takes a set of winners and losers from observed interactions and plots the probability of the dominant individual in an interaction winning given the difference in ... |
9c9086b82be9b15282a1db10a69758c5b25b0b53 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/mipfp/examples/confint.mipfp.Rd.R | f7f7d0987589aa6bb78ec5892dd18360af2b1435 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 741 | r | confint.mipfp.Rd.R | library(mipfp)
### Name: confint.mipfp
### Title: Computing confidence intervals for the mipfp estimates
### Aliases: confint.mipfp
### Keywords: multivariate
### ** Examples
# true contingency (2-way) table
true.table <- array(c(43, 44, 9, 4), dim = c(2, 2))
# generation of sample, i.e. the seed to be updated
seed... |
5afb2415c0f0396e3521c60461278be423e9ca2b | 5ffa646540a7a377795a5bf93bdc2f269605932d | /R/build_site.R | d51db8d34f599aa2e8994264337b04a64f56c61d | [] | no_license | melanie-demeure/stateoftheRinRennes | ec852091d9f0b29860f7b4b4c99b380445797ebd | b1256229b4c645e1dafa4ff8d31164c2d9d35b93 | refs/heads/master | 2022-12-23T02:13:12.459567 | 2020-09-28T13:47:35 | 2020-09-28T13:47:35 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 287 | r | build_site.R | ### Given the problems encountered with lapply in xaringan files generation, avoid laply and go for a loop
for(f in list.files('_posts/', recursive = TRUE, pattern = '.Rmd',
full.names = TRUE))
rmarkdown::render(f)
rmarkdown::render_site(encoding = 'UTF-8')
|
242b2489924eb0f34a91e11a08f140c3e99c57bd | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/lessR/examples/simCLT.Rd.R | bac3ab8ea992851ccad8e541afa30dee04c5e791 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 583 | r | simCLT.Rd.R | library(lessR)
### Name: simCLT
### Title: Pedagogical Simulation for the Central Limit Theorem
### Aliases: simCLT
### Keywords: central limit theorem
### ** Examples
# plot of the standardized normal
# and corresponding sampling distribution with 10000 samples
# each of size 2
simCLT(ns=1000, n=2)
# plot of t... |
0c37b98867a6fb9c50d51fec17e9d287bac277c0 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/IMIFA/examples/G_priorDensity.Rd.R | 75e5f5b4f31987543118f2f0cab609b19d425466 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 701 | r | G_priorDensity.Rd.R | library(IMIFA)
### Name: G_priorDensity
### Title: Plot Pitman-Yor / Dirichlet Process Priors
### Aliases: G_priorDensity
### Keywords: plotting
### ** Examples
# Plot Dirichlet process priors for different values of alpha
(DP <- G_priorDensity(N=50, alpha=c(3, 10, 25)))
# Non-zero discount requires loading the ... |
58b3e5ac6babfa7c85892f6c7e343ae38385f473 | 1e3728c33d28b9d6da73d9b5d0b195ae0f9e8cac | /Clustering/R Scripts/StackCols.R | 17911f404919efde3ad2b27487138aa192e42ab8 | [] | no_license | saurabh-devgun-iiitb/StackOverflowAnalytics | b2b705c3a6ec21550c07f30c4419e4ff00e4dc58 | 82d5a9dcd4adeaf14fb69952b3280e164dade702 | refs/heads/master | 2021-01-21T06:25:24.448403 | 2017-02-26T20:06:29 | 2017-02-26T20:06:29 | 83,233,293 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 687 | r | StackCols.R | tech <- read.csv(file.choose(),header=T)
View(tech)
#function for calculating Cramer's v
cramer <- function(y,x){
K <- nlevels(y)
L <- nlevels(x)
n <- length(y)
chi2 <- chisq.test(y,x,correct=F)
print(chi2$statistic)
v <- sqrt(chi2$statistic/(n*min(K-1,L-1)))
return(v)
}
#similarity matrix
sim <- matrix... |
701fac5cda5f3781ffcb4062d723f2df1fdeb0e6 | 652a00e139bf9cf1ad32ebbb812e195d6f1ce276 | /fetchGO.R | 06585422fb5186ff907eb118296e82529cf25f70 | [] | no_license | scalefreegan/R-tools | 7354dc5906b4082f8f097f182e6e8defeb996bc4 | 3b6bea3918e5f11b6f836ae582ff5fab5d9eadee | refs/heads/master | 2021-01-10T21:01:00.650652 | 2017-11-09T14:39:55 | 2017-11-09T14:39:55 | 2,478,837 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,247 | r | fetchGO.R | dlf <- function (f, url, msg = NULL, mode = "wb", quiet = F, ...)
{
err <- 0
if (mode == "wb" || !file.exists(f) || file.info(f)$size ==
118) {
if (!file.exists(dirname(f)))
try(dir.create(dirname(f), recursive = T))
if (!is.null(msg))
cat(msg, "\n")
err <- try(download.file(url, des... |
0150d7eb67c1444923ff6956bd6099c402777d8e | 9497ffe6f9feb5d740c18293844aa59d381c1a41 | /man/writeMgf.Rd | 87055e2ec2ad77765e93592b216632444d3f530b | [
"MIT"
] | permissive | ohgane/ShotgunLipidomicsR | 63efe1413c92d865665bfb9cabc67d6d90ba867a | b657c419eb2a4fd192c5b1e7db90fc79290f00ff | refs/heads/master | 2021-01-21T14:32:55.459687 | 2016-07-28T08:28:30 | 2016-07-28T08:28:30 | 59,251,794 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 603 | rd | writeMgf.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/writeMgf.R
\name{writeMgf}
\alias{writeMgf}
\title{A function that export mgf file from filename, precursor mz, and a peak table.}
\usage{
writeMgf(file, precursor, peak.table, charge = "+1")
}
\arguments{
\item{file}{A file name for MGF file... |
a11879ddfad2b64fa119be39e6ccdd977f6afc80 | 6cc2112b30258c1174fe3b2b1d7ca178ac769f16 | /metrics.R | 763f998ab0dd08abcffd559653060c034b09f956 | [] | no_license | tmuffly/obgynlit | 42c0f67c698b297839bc096ec10dfa9e3c07327a | 7988fa49ec989dd9c94baf526754a273c14655e1 | refs/heads/master | 2020-03-21T11:52:41.648343 | 2018-06-25T00:41:57 | 2018-06-25T00:41:57 | 138,526,037 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,075 | r | metrics.R | ## utilities ---------------------------------------------------------------
library(tidyverse)
library(fs)
library(futile.logger)
not_null <- negate(is_null)
`%<>%` <- magrittr::`%<>%`
## read data ---------------------------------------------------------------
#DATA_DIR <- path("/media", "garrett", "ExtraDrive1", "d... |
a4af4f7a1cd2fe235e0c41ad205b0725ddae5764 | 1e9d0ad51afcb498a1e784c832ebe0c6ad3d2d00 | /shiny/ui.R | 479be3b2d316ac6dab874ca1deeb7fdccebb9a0a | [
"MIT"
] | permissive | MatijaGH/APPR-2017-18 | 6c4d4a701c80bcee6f489c7cf8e7c47e8d8225c9 | b1e9e23cb03c6a815970ca9b5619e0d8b4737691 | refs/heads/master | 2022-02-18T05:12:04.648116 | 2019-08-21T09:19:03 | 2019-08-21T09:19:03 | 111,707,870 | 0 | 0 | null | 2017-11-22T16:29:34 | 2017-11-22T16:29:34 | null | UTF-8 | R | false | false | 1,706 | r | ui.R | library(shiny)
# shinyUI(fluidPage(
#
# titlePanel("Slovenske občine"),
#
# tabsetPanel(
# tabPanel("Velikost družine",
# DT::dataTableOutput("druzine")),
#
# tabPanel("Število naselij",
# sidebarPanel(
# uiOutput("pokrajine")
# ... |
f811307e216e20160eb3d0a27cad72c67902d572 | ba54c637f784a2b6ddf16697c58d483af7054f07 | /DMR.r | 3c2edc7f08676eb15cf11adb1c2f234d48d24b59 | [] | no_license | mfaisalshahid/Data-Mining | fa18bea3ed148c99520a0a73abdf30d291cf1892 | 828cfa79f764889f573b18f2c88fe4874c1e2467 | refs/heads/master | 2022-12-08T03:57:48.704055 | 2020-08-30T00:15:43 | 2020-08-30T00:15:43 | 291,365,480 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,540 | r | DMR.r | library(tidyverse)
library(PerformanceAnalytics)
library(caret)
housing_price <- read.csv("/Users/muhammadshahid/Desktop/ASS05_Data.csv")
df <- data.frame(housing_price)
# Part1
part1 <- function(df, p){
n <- nrow(df)
shuffled_df <- df[sample(n), ]
train_indices <- 1:round(p * n)
train <- shuffled_df[train_indi... |
98873415f87bd0c34ca16dc6ededb273a0e74b1a | ed009043cc51f25c4d2bcb1a365a9f5b9ad4c8b8 | /tests/r/mran/verify | b15da154761c64328d0a03649476ef4a96a970c7 | [
"BSD-3-Clause"
] | permissive | data-workspaces/dws-repo2docker | 2ad54b357e0d567be30111d7836ad2f405142905 | 4d8736d7e3d79b8cdfa1f644f590aa7fdede183b | refs/heads/master | 2022-05-07T02:22:28.559789 | 2022-03-10T15:35:11 | 2022-03-10T15:35:11 | 209,244,059 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 203 | verify | #!/usr/bin/env Rscript
library('testthat')
print(version)
# Fail if MRAN isn't the configured CRAN mirror
if (!(startsWith(options()$repos["CRAN"], "https://mran.microsoft.com"))) {
quit("yes", 1)
}
| |
803f1705ccb194cfd29154bc5d9ce399d9c950d1 | 8b60c33ca0d37d67a0ee3ccb1aa464fec537ccfc | /code/DataPreparation.R | fa15909bc55943f48041852b1099cd5355697805 | [] | no_license | alicebalard/Article_IntensityEimeriaHMHZ | 7df0a14685d5bb84b9ae13020ee24b930e04974c | 82f6b424646645f4c7953c9f48c64e54020dd3c4 | refs/heads/master | 2022-10-02T20:27:12.079801 | 2022-09-14T11:06:29 | 2022-09-14T11:06:29 | 205,409,239 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,285 | r | DataPreparation.R | # Installation
## Packages
list.of.packages <- c("parasiteLoad",
"bbmle",
"devtools",
"optimx", # for bbmle it needs to be required(?)
"ggplot2",
"VennDiagram",
"fitdistrplus", # evaluate... |
1c9895f06e47e22f749460a4f8c02706fab6a58b | 68b7f425408cb4188dccf7c91558370c6a91ae04 | /ORIGAMI/man/make_map.Rd | 671b6b518062197626a6097022f7864572f74384 | [] | no_license | qlu-lab/ORIGAMI | 19af8636263a433088fbc1d228541e0ba1ee5d52 | 8c317adeb59f27c47bae9c1c3e17cc10d22bebf2 | refs/heads/master | 2021-07-01T05:09:03.045889 | 2021-02-05T20:41:20 | 2021-02-05T20:41:20 | 220,383,273 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 482 | rd | make_map.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/make_map.R
\name{make_map}
\alias{make_map}
\title{make_map}
\usage{
make_map(chr, ref_file, rs_file, output_path)
}
\arguments{
\item{chr}{chromosome number}
\item{ref_file}{Ref file of your vcf data}
\item{rs_file}{Reference file contains... |
a64a2a351790e0c3865fc4a4a4ae0de5a42a337c | 6fb04083c9d4ee38349fc04f499a4bf83f6b32c9 | /man/createView.Rd | ac737115db7d841fd02d290962b2d39b5cd5440d | [] | no_license | phani-srikar/AdapteR | 39c6995853198f01d17a85ac60f319de47637f89 | 81c481df487f3cbb3d5d8b3787441ba1f8a96580 | refs/heads/master | 2020-08-09T10:33:28.096123 | 2017-09-07T09:39:25 | 2017-09-07T09:39:25 | 214,069,176 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 571 | rd | createView.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/constructAbstractSQL.R
\name{createView}
\alias{createView}
\title{Create View}
\usage{
createView(pViewName, pSelect, pDatabase = getOption("ResultDatabaseFL"), ...)
}
\arguments{
\item{pViewName}{Name of view}
\item{pSelect}{SELECT clause ... |
1d682bfdaf8b2fcc22549be9d7aac99dc5dfd089 | 857a7f4229065a77df1c5b856530b7db880255f0 | /lib/confusionMatrix.R | 66c8d386a7f65ea35a120622d39ea9ca17e47222 | [] | no_license | XJieWei/Fall2018-Project4-sec1-grp7 | e43758bc3e0e2dabb354674fbbaa9bf28a028d01 | 40d15604f8ea5d311336fa057ec592c4e02dc781 | refs/heads/master | 2020-04-10T18:26:52.042257 | 2018-11-29T02:52:38 | 2018-11-29T02:52:38 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,514 | r | confusionMatrix.R | # library(stringr)
# library(tm)
# library(dplyr)
# library(tidytext)
# library(broom)
commonMistakes <- function(truthTrain, ocrTrain){
groundTruth <- array(NA, c(1, length(truthTrain)))
for(x in 1:length(truthTrain)) groundTruth[,x] <- readChar(truthTrain[x], file.info(truthTrain[x])$size)
groundTruth <- st... |
31bd4781a4c04d03426edb35c9ce5f1aa487072d | 4346f0677cfd7f8994a34eb105fbb8459e0da810 | /man/checkBreakPoints.Rd | 28f7e543b93f1fdfa16068d47060cc0e1aa86fa1 | [] | no_license | cran/handwriter | cd5ae5358c81b96d34e11fd2bc7964a1489c9885 | ae51bdcde5692e5d51a3035049517e5a11e5b508 | refs/heads/master | 2023-07-12T18:13:37.321916 | 2021-08-16T15:20:02 | 2021-08-16T15:20:02 | 393,098,094 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 733 | rd | checkBreakPoints.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/JunctionDetection.R
\name{checkBreakPoints}
\alias{checkBreakPoints}
\title{checkBreakPoints}
\usage{
checkBreakPoints(candidateNodes, allPaths, nodeGraph, terminalNodes, dims)
}
\arguments{
\item{candidateNodes}{possible breakpoints... |
781e44a6a91014443466ffb429f9214d829e8d06 | d62d9ea2f6aa749fa48455bddbd3208279ce6449 | /man/plot_diet.Rd | bf408f307a668a6ef982d30593028633b5f39901 | [] | no_license | jporobicg/atlantistools | 3bffee764cca1c3d8c7a298fd3a0b8b486b7957e | 75ea349fe21435e9d15e8d12ac8060f7ceef31a2 | refs/heads/master | 2021-01-12T03:06:55.821723 | 2017-05-26T04:03:33 | 2017-05-26T04:03:33 | 78,160,576 | 1 | 0 | null | 2017-05-25T23:35:23 | 2017-01-06T00:51:21 | R | UTF-8 | R | false | true | 2,184 | rd | plot_diet.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot-diet.R
\name{plot_diet}
\alias{plot_diet}
\title{Plot contribution of diet contents for each functional group.}
\usage{
plot_diet(bio_consumed, species = NULL, wrap_col = "agecl",
combine_thresh = 7)
}
\arguments{
\item{bio_consumed}{C... |
8683f96091680eccc87e2588b34dae549a3243e6 | 6a28ba69be875841ddc9e71ca6af5956110efcb2 | /Schaum'S_Outline_Series_-_Theory_And_Problems_Of_Statistics_by_Murray_R._Spiegel/CH2/EX2.2.15/Ex2_2_15.R | 3d84d065092b03c2014147c990fe1bbf73bf4e4e | [] | permissive | FOSSEE/R_TBC_Uploads | 1ea929010b46babb1842b3efe0ed34be0deea3c0 | 8ab94daf80307aee399c246682cb79ccf6e9c282 | refs/heads/master | 2023-04-15T04:36:13.331525 | 2023-03-15T18:39:42 | 2023-03-15T18:39:42 | 212,745,783 | 0 | 3 | MIT | 2019-10-04T06:57:33 | 2019-10-04T05:57:19 | null | UTF-8 | R | false | false | 622 | r | Ex2_2_15.R | #PAGE=50
a=c(250,260,270,280,290,300,310)
b=c(259.99,269.99,279.99,289.99,299.99,309.99,319.99)
c=c(a,320)
c
n=c(8,10,16,14,10,5,2)
n=c(n,0)
n1=sum(n)
n4=rep(c,n)
n4
d0=n[7]
d1=n[7]+n[6]
d2=d1+n[5]
d3=n[4]+d2
d4=n[3]+d3
d5=n[2]+d4
d6=n[1]+d5
d=c(0,d0,d1,d2,d3,d4,d5,d6)
d=rev(d)
d
c
e=c('or more',... |
6650dd7f06d72c15dd6638df2d157a72882d7797 | 8b394510187514efb88c8e0c4608a151e221dbc7 | /ui.R | 4ecbf765088c3b56142881193b850eecdde4905d | [] | no_license | itoDreamer/apmTool2 | 98d76772baa5cc0b879940e43940d30af4c84164 | 343ce11a7ca5d38a1239aa400e9721654b2d992e | refs/heads/master | 2022-11-19T05:39:07.586401 | 2020-07-20T19:36:52 | 2020-07-20T19:36:52 | 279,189,620 | 0 | 0 | null | 2020-07-13T02:28:07 | 2020-07-13T02:28:07 | null | UTF-8 | R | false | false | 23,396 | r | ui.R | library(shinydashboard)
library(DT)
library(shiny)
library(shinyWidgets)
library(rhandsontable)
library(quantmod)
shinyUI(dashboardPage(skin = "black" ,
dashboardHeader(title = "Portfolio Allocation Demo"),
dashboardSidebar(
sid... |
cb00563cde3ef9a9052c84f9bf89d8f24af3d4b2 | 0a906cf8b1b7da2aea87de958e3662870df49727 | /biwavelet/inst/testfiles/rcpp_row_quantile/libFuzzer_rcpp_row_quantile/rcpp_row_quantile_valgrind_files/1610555316-test.R | c3477f4f62ba4b3efdaf101d5e609c503dc33a69 | [] | no_license | akhikolla/updated-only-Issues | a85c887f0e1aae8a8dc358717d55b21678d04660 | 7d74489dfc7ddfec3955ae7891f15e920cad2e0c | refs/heads/master | 2023-04-13T08:22:15.699449 | 2021-04-21T16:25:35 | 2021-04-21T16:25:35 | 360,232,775 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 319 | r | 1610555316-test.R | testlist <- list(data = structure(c(-8.65145885556673e+303, 2.27541883785622e-317, 1.32548933609124e-309, 1.67141905462553e-112, 3.52953630161737e+30, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = 5:6), q = 0)
result <- do.call(biwavelet:::rcpp_row_quantile,testlist)
str(result) |
c6ae6917bed48876f97b015d193708657b78bc25 | 7fd95b701e50edbe16f9bb349ad240acf2a1df73 | /scripts/results.R | bdb34b9504d3d562b0cade48a7a211fbedc29f17 | [] | no_license | ryali93/SedimentYield | 75817d6868ea0e13d9bd0cbdf95f931874c6f44d | e93216a3df2cc1689e992e80138d1b0b14cf9417 | refs/heads/master | 2020-04-07T13:59:32.709522 | 2019-06-09T11:31:30 | 2019-06-09T11:31:30 | 158,430,004 | 4 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,387 | r | results.R | # rm(list=ls())
library(dplyr)
library(reshape2)
library(ggplot2)
df = read.csv("E:/TESIS/process/results.csv", sep = ",", header = T)
df2 = df %>% filter(ts != "1981-01-01" & ts != "1982-01-01" & ts != "1983-01-01" & ts != "1985-01-01" & ts != "2016-01-01")
df3 = df2 %>% select(-r_c3_ls1_sdr1, -r_c3_ls1_sdr2, -r_c3_... |
d0397fd95d2fd2e0de3017cdf946643982a91368 | 60a99dc425d9edca7b3dec562f5cf6367d9c61ec | /prettyGraphs/man/contributionBars.Rd | 81b09b641f5fbb4d31bbde595defa80f1385894f | [] | no_license | LukeMoraglia/ExPosition1 | e7718ae848608f1dc3934513c6588f53f2c45a7f | a69da6c5b0f14ef9fd031b98c3b40b34dad5240f | refs/heads/master | 2022-12-31T17:45:10.909002 | 2020-10-22T19:45:49 | 2020-10-22T19:45:49 | 255,486,130 | 0 | 1 | null | 2020-10-22T18:08:38 | 2020-04-14T02:01:12 | R | UTF-8 | R | false | false | 1,779 | rd | contributionBars.Rd | \name{contributionBars}
\alias{contributionBars}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
contributionBars
}
\description{
Produces bar charts for multivariate analyses. Plots the contribution to the variance from each data point for upwards of two axes (components).
}
\usage{
contribution... |
a3e516e5b4d26ba90f788888f733e2624fbd8566 | 2e49deee0b0e8060e08af969baa9b1fc0d8a6c77 | /app.R | 228a65d6b299f583f6e9cfa7aff64a9a9ca440e7 | [] | no_license | DrMattG/AcademicCVShinyDashboard | 8d1d0e49c6633336ac9fe13cc0f7cebb3bfc8388 | e14ff6ea0f13abc04ab8fa1922cef287a3a1f9e2 | refs/heads/master | 2021-07-17T02:56:27.074653 | 2020-08-04T12:30:11 | 2020-08-04T12:30:11 | 197,767,565 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,502 | r | app.R | #Source the datafile (updates it)
source("code/Data_save.R")
updateData()
# load the required packages
library(shiny)
require(shinydashboard)
library(tidyverse)
library(scholar)
library(timevis)
library(tm)
library(wordcloud)
library(rsconnect)
library(readr)
###########################
#Build shinyapp
#UI
ui <- dashb... |
2835e9256613118a9a3cebab991caef3e433ff30 | 0d5fb58c69e80a16f7ce8496bff1d37dd5040763 | /water_param_DEoptim.R | f4feba52ee6230a844a32fd766d4f694686ff3b4 | [] | no_license | kevinwolz/hisafe-calibration | b64c731b16cc811ecc58b0867682a43e1a9e9249 | 46067ed2200d73c0daef06017f7eab91274ea865 | refs/heads/master | 2023-07-14T09:06:49.274190 | 2019-03-23T19:40:46 | 2019-03-23T19:40:46 | 110,268,940 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,913 | r | water_param_DEoptim.R | ### hisafe water module parameter optimization
### Author: Kevin J. Wolz
library(hisafer)
library(tidyverse)
library(parallel)
library(DEoptim)
library(plotly)
N.ITER <- 3
TRACE <- TRUE
YEARS <- 1994
METHOD <- "DISCRETE" # TOTAL
CROPS <- c("durum-wheat-restinclieres", "weed-restinclieres", "rape", "winter-pea")
B... |
0cfdf419f76a2b42087ab29977f6405d033df44e | 62c1dd454d9ce2046792545d1cbcce0af0285d93 | /R/preview.R | 17c5b60eab287bf010a45407ff091efaa971a5b5 | [] | no_license | davidallen02/employment-situation | a9ab3a0a024612be58e4e15ccbb1e2b3f134f73b | ff9a8805fc72a1a65cdccae5cb693e2f1766fe71 | refs/heads/master | 2021-07-14T03:41:49.476051 | 2021-02-01T17:15:58 | 2021-02-01T17:15:58 | 232,154,779 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,210 | r | preview.R | library(magrittr)
# source('./R/functions/read_data.R')
# source('./R/functions/ppt_output.R')
consensus <- pamngr::get_data("nfp tch", flds = "BN_SURVEY_MEDIAN") %>%
dplyr::left_join(pamngr::get_data('usurtot', flds = "BN_SURVEY_MEDIAN"), by = "dates") %>%
dplyr::left_join(pamngr::get_data('ahe yoy%', flds = "BN... |
039b0625b3377f35562245f8f7eca7320ee5589a | 00be44c6e49e7f0e948bb202457240467665480e | /R_templates/meta_bag.R | 29defa2d657f4aec16cb38adf60dd2dd6223f31e | [] | no_license | AkiraKane/scharf-personal | b9469d76e026255283f99d66c5cb0e17456bf8b5 | b6b6560bc8ac5033871e6e64cb2920b6b14f30bd | refs/heads/master | 2021-01-19T20:58:07.745222 | 2016-09-22T15:12:26 | 2016-09-22T15:12:26 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 948 | r | meta_bag.R | meta_bag <- function(
Xtrain, # This is a matrix, contains train data, data_cols only
Xtest, # This is a matrix, contains train data, data_cols only
y, # contains target vars
model_dir, # we will make this directory if it doesn't exist
n_models, # to... |
73fadd4dd63097d2a007f20704cbdb566337920d | 55c2eaf5f65b863bf6efd0cd5c6f29dce85dac30 | /R/utils.R | a3f4ba6020b305780ef0008895c2a1229785da66 | [] | no_license | renanlf/distrstats | 244d6209ae67ae77ac81c9299b2b2d136ee49b36 | f2d09708ecf3cb6482595963291158c04f977384 | refs/heads/master | 2023-06-30T12:09:02.085495 | 2021-08-07T02:08:51 | 2021-08-07T02:08:51 | 393,548,604 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 280 | r | utils.R | as.dataset <- function(name, values){
list(
name = name,
values = values
)
}
as.distribution <- function(name, pdf, cdf, nparams, lower, upper){
list(
name = name,
pdf = pdf,
cdf = cdf,
nparams = nparams,
lower = lower,
upper = upper,
)
}
|
1b753bae631f20d554bcdb283cc4ce5f03443280 | 9320966521bd97b3eb88207fe53b4054568a45d2 | /OUTROS/IC/PROJETOS/Classificador-IMDB/RECOMMENDER-IMDB/Rmd-RF/outros/q10.R | d21d7677c549d73a003ad993233ccd4df607cacd | [] | no_license | eupimenta/textmining_pt | e70a6b7ff901953a479f5bf3957572f83ed61773 | 2b3a45f92e5be28bbbd31134b998b27721072b59 | refs/heads/master | 2020-04-29T01:35:08.215762 | 2019-06-19T17:40:56 | 2019-06-19T17:40:56 | 175,735,476 | 0 | 0 | null | 2019-06-19T17:40:57 | 2019-03-15T02:37:13 | HTML | UTF-8 | R | false | false | 828 | r | q10.R | n = dim(missing_data)[1]
dat <- missing_data
#Create a function to generate a continuous color palette
rbPal <- colorRampPalette(c('red','blue'))
#This adds a column of color values
# based on the y values
dat$Col <- rbPal(10)[as.numeric(cut(dat$percent_missing,breaks = 10))]
plot(dat$percent_missing,dat$percent... |
8640592da1a6439fd80eaf9d3a6e0597dcc1dace | f67642256737632b0e4a794af02f2df1aee726b8 | /man/is.diag_resid.Rd | 11be1a62647554794eca1f684d6611b789c9efb8 | [] | no_license | SMAC-Group/exts | 0a430cc0df20e85903e55eb1ed5c8be76c3c6d8a | 0aa78daff83dd4dca9fc3e166afbd2a3d726966d | refs/heads/master | 2020-04-17T05:48:48.245078 | 2016-11-14T02:14:00 | 2016-11-14T02:14:00 | 67,654,379 | 0 | 2 | null | null | null | null | UTF-8 | R | false | true | 353 | rd | is.diag_resid.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utilities.R
\name{is.diag_resid}
\alias{is.diag_resid}
\title{Check is class}
\usage{
is.diag_resid(x)
}
\arguments{
\item{x}{A \code{diag_resid} object}
}
\value{
A \code{boolean} indicating \code{TRUE} or \code{FALSE}
}
\description{
Perfor... |
14c37ed30811d817d1da2be04b559863096ab8d8 | 7a95abd73d1ab9826e7f2bd7762f31c98bd0274f | /meteor/inst/testfiles/ET0_ThornthwaiteWilmott/AFL_ET0_ThornthwaiteWilmott/ET0_ThornthwaiteWilmott_valgrind_files/1615830926-test.R | fdbf3182bef6c48035d201ce9eb1207fd155e2f8 | [] | no_license | akhikolla/updatedatatype-list3 | 536d4e126d14ffb84bb655b8551ed5bc9b16d2c5 | d1505cabc5bea8badb599bf1ed44efad5306636c | refs/heads/master | 2023-03-25T09:44:15.112369 | 2021-03-20T15:57:10 | 2021-03-20T15:57:10 | 349,770,001 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 545 | r | 1615830926-test.R | testlist <- list(doy = c(3.01409667740156e-243, -3.20180237041553e-60, 3.01425161743895e-243, NaN, -6.8576842040592e+303, 1.36446060005412e-317, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0),... |
b2c9cddfe12e938723d4671f50ebaba4255ff16e | de83e0fb6c3ce2dd4c2dda13cc54f33fb03cfc5a | /packages/BfgGiStats/man/differential_gi_analysis.Rd | 1ac3f90504e33ff8a63a84881a0e5e81616ccb52 | [] | no_license | a3cel2/BFG_GI_stats | 1636daadad2ec5e2957be3f0fcb93ae00a58f882 | 365561db2ccb6a097961045bb745d22e4f5687ee | refs/heads/master | 2021-05-08T07:30:27.955184 | 2018-04-28T23:07:30 | 2018-04-28T23:07:30 | 106,863,220 | 0 | 1 | null | 2018-01-29T16:32:24 | 2017-10-13T19:06:04 | R | UTF-8 | R | false | true | 1,134 | rd | differential_gi_analysis.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/differential_gi_calls.R
\name{differential_gi_analysis}
\alias{differential_gi_analysis}
\title{Differential Genetic Interaction analysis}
\usage{
differential_gi_analysis(gi_data, fdr_cutoff = 0.05, delta_gi_cutoff = 0,
require_sign_change... |
2262e6a6303cd0cafdbdc95b757a4c70f0e6378b | 0710a223ae6b7bc07b2e9dcfbd7e166256715c54 | /chelu_mapamundi.R | e1d047f0e038cfe7e000ba63b87887e1eb824aa2 | [] | no_license | JuanmaMedina/random_projects | fa324912b61e3786744e68bdb0e1cdd4e4f18698 | a72a6962ed58681cbdf4ecc498f6e55229c092b0 | refs/heads/master | 2020-09-21T13:54:47.960251 | 2019-11-29T08:35:46 | 2019-11-29T08:35:46 | 224,808,202 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,394 | r | chelu_mapamundi.R | # Create data frame with iso3 country codes and a drug measure
# x data frame (DF) edition instructions:
# Step 1: Identify and write the iso3 codes of interest countries in the "country" column
# Step 2: Associate countries with desired drug measure in the "drug_measure" column
x <- data.frame(country = c("AUS", "JP... |
1427110e0901230ec30fa908cb05659d93978115 | 72d9009d19e92b721d5cc0e8f8045e1145921130 | /RobustCalibration/man/rcalibration_MS.Rd | c60c8c46626e3dea4a530c96eb31dc1b68a7d29c | [] | no_license | akhikolla/TestedPackages-NoIssues | be46c49c0836b3f0cf60e247087089868adf7a62 | eb8d498cc132def615c090941bc172e17fdce267 | refs/heads/master | 2023-03-01T09:10:17.227119 | 2021-01-25T19:44:44 | 2021-01-25T19:44:44 | 332,027,727 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 10,361 | rd | rcalibration_MS.Rd | \name{rcalibration_MS}
\alias{rcalibration_MS}
%\alias{show.rgasp}
\alias{rcalibration_MS-method}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{ Setting up the robust Calibration model for multiple sources data
%% ~~function to do ... ~~
}
\description{
%% ~~ A concise (1-5 lines) description ... |
ebd180019db5f38e1fd9d8368f533de27f583dc9 | 2cc39aa3e019de9ab77124a6c812ec48934929ad | /R/template.R | c6b3e3a9645cc229d7c8d087f6337eb7ad6addb5 | [] | no_license | cran/liGP | d997e4794866b42cca165c3c11397b3ba80d98a9 | b79f54ecd535f48f4e4c390925302380bf5deb25 | refs/heads/master | 2023-06-15T12:07:39.187428 | 2021-07-17T05:00:02 | 2021-07-17T05:00:02 | 382,082,393 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 16,481 | r | template.R | eps <- sqrt(.Machine$double.eps)
## build_ipTemplate:
##
## Creates an inducing points design optimized with ALC or wIMSE,
## then is returned centered at the origin
build_ipTemplate <- function(X = NULL, Y = NULL, M, N, theta = NULL, g = 1e-4,
method = c('wimse','alc'),
... |
f3cbd9c397377e6b379b77469d630f5ed6b882b2 | 2d1866e3a065b074f7a0a8029d170f204c9faa18 | /inst/doc/indexing.R | 0d7213d886957091ea49e2e0fb0f2b3ef8f23b15 | [
"CC0-1.0",
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-public-domain-disclaimer"
] | permissive | cran/nhdplusTools | 4f5af6385b022269d5e71407f76faaaadac6de25 | ce7303826ccc687527ef6ca8292df92aba9253fd | refs/heads/master | 2023-09-03T19:21:32.397941 | 2023-08-31T07:40:05 | 2023-08-31T09:30:59 | 236,631,877 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,946 | r | indexing.R | ## ----setup, include = FALSE---------------------------------------------------
library(nhdplusTools)
local <- (Sys.getenv("BUILD_VIGNETTES") == "TRUE")
if(local) {
cache_path <- file.path(nhdplusTools_data_dir(), "index_v")
} else {
cache_path <- tempdir()
}
knitr::opts_chunk$set(
collapse = TRUE,
... |
850d667a57ab8de922a055d70344b1ff18786282 | 4231f527b668f4f082f617c679fef87cedb15bfa | /R/models-nlme.R | ce56f497f99716879750f5e5f1b4558b4ee96692 | [
"MIT"
] | permissive | camroach87/1901-nlmets | 86329614e5d543e6d8a5ad4ccb56c9ae5ee09f89 | bd72f855c36e989c3537f93d4adca8e27f7cd652 | refs/heads/master | 2023-01-29T20:02:53.934713 | 2020-12-11T02:37:56 | 2020-12-11T02:37:56 | 218,911,330 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,139 | r | models-nlme.R | # Note: predict.lme throws errors if formula is created in `lme` function call.
# Need to use eval and substitute to get around this.
# Reference: https://stat.ethz.ch/pipermail/r-help/2003-January/029199.html
fit_ind_lm <- function(data) {
output <- data %>%
group_by(bid) %>%
nest() %>%
mutate(fit =... |
887ed549f86811716c950d500388bf65f7bfab42 | b06a918eb2c1a3b147a124dd204a41dbbf12ed46 | /man/print.FSA.Rd | 3bc79fa15c9c0c41ffa57595c6b54a14b9e7bbf8 | [] | no_license | joshuawlambert/rFSA | 712cd31dfa0ba7641b20d9120227e328d4dc7c6b | b0986bb2534f550f6b6a4215d107254c370910d9 | refs/heads/master | 2021-07-13T14:13:30.222459 | 2021-06-30T16:49:59 | 2021-06-30T16:49:59 | 95,580,239 | 10 | 0 | null | null | null | null | UTF-8 | R | false | true | 726 | rd | print.FSA.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/print.FSA.R
\name{print.FSA}
\alias{print.FSA}
\title{Printing function for FSA solutions}
\usage{
\method{print}{FSA}(x, ...)
}
\arguments{
\item{x}{FSA object to print details about.}
\item{...}{arguments to be passed to other functions.}
... |
35f4b88be92e09db93921f9dc737fcc0d6479da2 | 303ecdc998923dc101dfc42b8dbf42853ce7a7ec | /man/ClassifierModels.Rd | 88bb2589c494fc9c905b76679009591799888db6 | [] | no_license | mattdneal/FAIMSToolkit | 7e2640eb979110c2fca1cad639beb78fb9b25be4 | 751bfba992587bb7e5edba272a3890b088e19e33 | refs/heads/master | 2021-01-11T17:37:52.367113 | 2018-12-01T13:54:33 | 2018-12-01T13:54:33 | 79,808,086 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,071 | rd | ClassifierModels.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/crossValidation.R
\name{ClassifierModels}
\alias{ClassifierModels}
\title{Run a set of classification models on input training, test data sets}
\usage{
ClassifierModels(data.train, targetValues, data.test, models, kFolds = 2,
repeats = 5, t... |
5c52a7abad1ebabf7ff9d7eccefe0fc6b0741c95 | 7da6f203762c9c23d83ca262cf1ae2d03d51b228 | /03_gacd/w1/quiz.R | 318a1cd0c1289ddcf3c7362b8d9860637f6d14bf | [] | no_license | josoriov/ds-coursera | ace55d97b44707283bd0a4739a4829ce0bdce41c | 7018e0af76ba87cf7887636070bc8980393ed3fa | refs/heads/master | 2022-11-16T02:10:58.242363 | 2020-07-15T22:22:01 | 2020-07-15T22:22:01 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 425 | r | quiz.R | # 1
# dat <- read.csv("housing.csv")
# a <- dat(dat, VAL==24)
# Rta = 53
# 3
# RTA = 36534720
# 4
require(XML)
dat <- xmlParse("http://d396qusza40orc.cloudfront.net/getdata%2Fdata%2Frestaurants.xml")
xml_data <- xmlToList(dat)
xml_data <- xml_data[[1]]
a <- unlist(lapply(xml_data, function(x) x$zipcode == "21231"... |
7df1aa47af4e55d0b35de46ba3a520a5778dbfd8 | db7430d5693c5aa8e9f9f7affd41df058407d084 | /man/RcmdrPlugin.RiskDemo-package.Rd | d72ad4cb6d9eb4586cde09dda129ba450eb97e84 | [] | no_license | arolluom/RcmdrPlugin.RiskDemo | 8fbb654f97b764099dc7f7bd7991d4a0d730baf4 | a66816c9f30ebd7b398ac5cb8a01c951ff0b5c05 | refs/heads/master | 2021-01-15T19:59:54.356246 | 2017-08-09T17:45:30 | 2017-08-09T17:45:30 | 93,251,917 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 647 | rd | RcmdrPlugin.RiskDemo-package.Rd | \name{RcmdrPlugin.RiskDemo-package}
\alias{RcmdrPlugin.RiskDemo-package}
\alias{RcmdrPlugin.RiskDemo}
\docType{package}
\title{
R Commander Plug-in for Risk Demonstration
}
\description{
R Commander plug-in to demonstrate various actuarial and financial risks. It includes valuation of bonds and stocks, portfolio optimi... |
152ea90956166573dd68f3c9a2d6849996690cc3 | 9721b7e97328faf3e4dafaa24d70310129d52b01 | /R/permcoefs.plsRnp.R | e73e89ae4f8e1730b37b051b24e888b5b55c995b | [] | no_license | kongdd/plsRglm | 77dd10e804ec3606d914aae22a863a497497cd18 | dfa4e54ea02bca8bf04d29bb65dc7dba611927c9 | refs/heads/master | 2022-02-19T20:26:29.672362 | 2019-10-01T10:41:55 | 2019-10-01T10:41:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 444 | r | permcoefs.plsRnp.R | permcoefs.plsRnp <- function(dataRepYtt,ind,nt,modele,maxcoefvalues,wwetoile,ifbootfail){
dataRepYb=dataRepYtt[ind,1]
Tb=dataRepYtt[,-1]
tempCb=try(solve(t(Tb)%*%Tb)%*%t(Tb)%*%dataRepYb,silent=TRUE)
tempcoefs <- rbind(Intercept=0,wwetoile%*%tempCb)
Cond <- FALSE
try(Cond<-is.numeric(tempcoefs)&all(abs(tempcoefs... |
5b3b0c37e5dfcaa1ce2697953b8caace0a0f0714 | 7a9a8fb85481a80124bb1004eb3f4cfb46cdbede | /modeling1.R | 8318789beb43987ee910f03eba8a4a6748738ec1 | [] | no_license | xinyizhao123/Predicting-Future-Ambient-Ozone | 6459a9eef144bbf68416522f1987cf60f87af6bd | 1b682e4fcc16f443b4d3d8c9216cb5f823ac2986 | refs/heads/master | 2020-05-25T14:58:23.133324 | 2016-10-06T00:52:51 | 2016-10-06T00:52:51 | 69,671,822 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 13,937 | r | modeling1.R | #######################################################
# This program is to perform modeling for the dataset
# Programmer: Xinyi Zhao
# Date: 01/23/2016
#######################################################
#setwd("C:/Users/zhaohexu/Dropbox/Ozone project")
#setwd("C:/Users/Hitomi/Dropbox/Ozone project")
#in... |
19036c562e6420da1fa3e897142d0b746d0e74f9 | 8dcb923dea78fa398f185c06b5975d259a29f7c3 | /modules/met_data/prepare_tair_rh_par_data.R | fbdc0af8ef67fe6ce038eb1e78bb04a78470a045 | [] | no_license | mingkaijiang/EucFACE_Carbon_Budget | ce69f2eb83066e08193bb81d1a0abc437b83dc8d | 11abb2d6cd5e4121879ddecdf10ee5ba40af32ad | refs/heads/master | 2020-09-03T03:43:00.823064 | 2020-01-15T02:14:51 | 2020-01-15T02:14:51 | 219,377,500 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,140 | r | prepare_tair_rh_par_data.R | prepare_tair_rh_par_data <- function(timestep) {
#### Download the data - takes time to run
myDF <- download_tair_rh_par_data()
#### Assign ring information
myDF$Ring <- sub("FACE_R", "", myDF$Source)
myDF$Ring <- sub("_T1.*", "", myDF$Ring)
myDF$Ring <- as.numeric(myDF$Ring)
myDF <- ... |
aed6651573253b01213e25d6526e551157f12107 | 6baba64a7bdb5879768da2302a23608be28cf3ee | /FormerLabMembers/Linh/sdmt_analyses/funcs_long/find_cpt.R | a2608976e4e850d41bda8af215f8fd646c95094e | [] | no_license | bielekovaLab/Bielekova-Lab-Code | 8db78141b6bebb0bbc08ea923655a676479992fa | 369db2455344660e4012b605a4dc47c653a5c588 | refs/heads/master | 2023-04-20T01:01:50.556717 | 2021-05-04T12:44:37 | 2021-05-04T12:44:37 | 261,584,751 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 570 | r | find_cpt.R | find_cpt <- function(data, patient, c_input, b0_input, b1_input) {
pat <- patient
y <- data %>% filter(PID==pat) %>% .$y
x <- data %>% filter(PID==pat) %>% .$x
mod <- nls(y~fx(x,c,b0,b1), start=c("c"= c_input,"b0"= b0_input,"b1"= b1_input),
control=nls.control(warnOnly = TRUE,minFactor = 1e-2... |
2e009cfcda6c77e24f9832625f83a08f445bbf8d | 0a5932d0914152af939fd112158ac9f73901e41e | /R/compare_sources.R | a128f2d82c79136c9753c5027ec95b6f26b8cf97 | [] | no_license | andrewcparnell/simmr | 558b745360b13b413eb895585161c8e38e09cda2 | 8967f5d9800c20d3817cc2e8cf5195e96c6520a6 | refs/heads/master | 2023-08-31T10:10:27.187056 | 2023-08-21T10:13:21 | 2023-08-21T10:13:21 | 40,361,152 | 21 | 8 | null | 2023-08-01T10:53:37 | 2015-08-07T13:13:05 | R | UTF-8 | R | false | false | 7,153 | r | compare_sources.R | #' Compare dietary proportions between multiple sources
#'
#' This function takes in an object of class \code{simmr_output} and creates
#' probabilistic comparisons between the supplied sources. The group number can
#' also be specified.
#'
#' When two sources are specified, the function produces a direct calculation
#... |
9243ba678025e54bbcb7b7a300dc99c55b32864c | a206f33c8cbd90abf2f400f79b233b4e56c89f23 | /clusterizacion/clusterizacion.R | 0d93c7b54b47795dbc30029c3d871070dfba9b94 | [] | no_license | andresrabinovich/algoritmos-geneticos | 60a403860fcad3932e5f18bad23a6ac9312c12f1 | 6b3923981c2f51ed735451f735dd12e1c63a0d75 | refs/heads/master | 2021-01-10T13:46:18.419293 | 2015-07-15T12:53:51 | 2015-07-15T12:53:51 | 36,511,094 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,023 | r | clusterizacion.R | #TO DO
#VER COMO IMPLEMENTAR LA FUNCION SAMPLE EN C!
#///////////////
#CONFIGURACIONES
#///////////////
#---------------------------
#Configuraciones del dataset
#---------------------------
poblacion = 100;
pm = c(0.1, 0.1, 0.1); #probabilidad de mutacion
pc = 0.1; #probabilidad de single-point crossover
generacione... |
8ef100fa494ee797aea518908f34eb134ebfb440 | 0c55f047f3a80bb94c6a7ad050c9c44e60a73fb9 | /LogisticGrowth/remove_model_failures.R | 1e0043d87687ae9173d9e38152bd324db5f881a9 | [] | no_license | Tuc-Nguyen/HLF-Robot-Image-Analysis-2.1 | 3d2ab9476656ab9d2a4518512bb34c23da39381c | bdb652a1169fb2f66117ddda971e8fabe07dd037 | refs/heads/master | 2022-04-14T06:01:16.323714 | 2020-03-26T16:36:22 | 2020-03-26T16:36:22 | 250,310,692 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 866 | r | remove_model_failures.R | require(ggplot2)
modeled_file = "logistic_growth.tab"
classes = c("numeric","numeric","character","factor",
#Row Col Name Media
"factor","factor", "factor", "character",
# Temp Array(1-6) Condition Well
"character","character","character"... |
22857fe5f4beadf3e2af0f6eb99605a657cadcfc | 9d8b86b2a20d5fd3c31a3bce56e7f52312187be1 | /R/z.score.R | 0fab959d7a188948c3ddf463efb0479efdc00b15 | [] | no_license | hms-dbmi/Rcupcake | d4141be5394de83340f476392defa11477fda1ee | 2f87f7c771ceb0da7813a90529c973e1f028b6e8 | refs/heads/master | 2022-01-17T06:03:15.038438 | 2019-07-02T23:44:11 | 2019-07-02T23:44:11 | 81,849,992 | 2 | 5 | null | 2018-04-06T15:36:32 | 2017-02-13T17:08:40 | HTML | UTF-8 | R | false | false | 6,390 | r | z.score.R | #' Transform continuous in categorical variables and generates a new \code{cupcakeData} object.
#'
#' Given an object of class \code{cupcakeData}, it transforms continuous into categorical variable
#' applying Z-score. As a result a new \code{cupcakeData} object is generated. Note that if the number
#' of individuals ... |
27ad7a4ec2260a14cc4095ce803ce30e8367ada3 | 257cc65928167620b1d10ca750cd71ddac0452c5 | /SoundMetric_QDA.R | a6e22389bce9a2d974ee880d97ef2a4f60da686c | [] | no_license | kbellisa/MIR-sound-ecology | f9ab74230b4f4cac79a38063b23451fcb9d497d7 | aa94e088a89db786889b397673b60f11b3bbce4d | refs/heads/main | 2023-05-05T22:02:25.553297 | 2021-06-03T15:59:10 | 2021-06-03T15:59:10 | 373,556,602 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,898 | r | SoundMetric_QDA.R | ##################################################################################
# MIR Study (no removal of outliers)
# USES linear and quadratic discriminant analysis
# Research question? Can we use spectral features to determine soundscape class?
# Kristen Bellisario
# with additional help from Zhao Zhao, Cristan G... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.