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0d430dcdc0d15815a8bf0bf198e37040f9dd4504 | 8933d3a00e9d676cdd9a0e7155f33e76fb52cb44 | /association_test_wgs_wes/5b-match_wes2wgs.R | cffbdf9af6e90ed37e660ea5f0417f5bfd90b076 | [] | no_license | LeiChen0218/PhD_toolkits | 19fe47c90ebce1fadee5fb987e3d48ef63a34cf0 | c4c54f8b9ed16e5ba2eb6b961cc49be8f6211238 | refs/heads/master | 2020-12-28T09:52:59.450619 | 2020-02-04T19:20:47 | 2020-02-04T19:20:47 | 238,277,650 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,952 | r | 5b-match_wes2wgs.R | setwd('/Users/leichen/Desktop/Lab/Finmetseq_paper/3-Candidate_analysis/data/wes_match/')
library(ggplot2)
# read in wes results
bam1 <- read.table('cands.traits.bam1.txt', header = T)
bam2 <- read.table('cands.traits.bam2.txt', header = T)
meta <- read.table('cands.traits.r01_exon.meta.txt', header = T)
# read wes to... |
b41923d5eb99c0829fdf8d384090e76f4c6a1202 | 6fe5ae4a3f67f560f43e6343839d0a17ffa5181a | /R/multi_trial.R | 7aa3bac35af2dc353dcff510c8dacd0dfcc2ee8d | [] | no_license | cran/adaptDiag | 0c5901e53e0d119d959fe3e0e3b5553bb74d97e1 | d651b259304bb4b877a2070ae6826a76be2251da | refs/heads/master | 2023-07-10T10:29:09.351707 | 2021-08-17T06:20:14 | 2021-08-17T06:20:14 | 397,309,212 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 13,728 | r | multi_trial.R | #' @title Simulate and analyse multiple trials
#'
#' @description Multiple trials and simulated and analysed up to the final
#' analysis stage, irrespective of whether it would have been stopped for
#' early success or expected futility. The output of the trials is handled
#' elsewhere.
#'
#' @param sens_true sca... |
023fb5eec65de1fcb209c9543b3e5a7af9413b6f | 604209f18e54add484640e37a8d12636e7451540 | /man/get_single_Quandl.Rd | 39cfe81eac8e895dd656ce52a44a2252196f43bb | [] | no_license | msperlin/GetQuandlData | 5212b6eb9f984ccca3653c4fd83870a38cadc78e | 563edf8ace68111868bd0d4043d80f9bd32eead0 | refs/heads/master | 2023-02-23T13:00:19.433950 | 2023-02-15T12:26:25 | 2023-02-15T12:26:25 | 212,104,930 | 9 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,790 | rd | get_single_Quandl.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_guandl_series.R
\name{get_single_Quandl}
\alias{get_single_Quandl}
\title{Fetches a single time series from Quandl}
\usage{
get_single_Quandl(
id_in,
name_in,
api_key,
first_date,
last_date,
do_cache = TRUE,
order = "asc",
... |
dcd2fa72590af9e00024f9c5793ec414d8c35fe6 | 6141ec79d6d942783a2ee5eca2ed957b2b852b11 | /Scripts/GeometricMorphometrics.R | bea06ebc3983910746f50382e0bfa479d2b313c2 | [] | no_license | Moreau-Lab/MorphologyAndPCAs | adc56a53ea26cda2151379d6b81141a56fc4218c | 94593c7f1075061ab50c0690be959c636575d078 | refs/heads/main | 2023-03-24T19:46:20.387234 | 2021-03-22T17:32:54 | 2021-03-22T17:32:54 | 350,418,189 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,637 | r | GeometricMorphometrics.R | # Script for geometric morphometrics of ant head shapes.
# This script requires tps formatted landmark data for input. See the data folder for an example of what this looks like.
# Load the packages we will use:
library(geomorph)
library(tidyverse)
# All of the steps of the analysis are wrapped up in a single fun... |
06031e1128d3e711588b04336dac25903a11b33d | 005bb9edaf643be9c8548d803483628c80cc0225 | /second_fall_experiment/scripts/clay_R_scripts/analysis/model_psi_leaf/crap/predict_leafwp_noaddedvars.R | c4e395e8ae02b7a3876b93f08d03c337f7570493 | [] | no_license | sean-gl/2020_greenhouse | 16b35b6b035a1926dc8858c7d0b2eba6b8dbe864 | 691c3923c75eea1bd57b8d218b343e8fdc10c33c | refs/heads/master | 2021-05-22T00:22:46.456072 | 2020-05-25T17:28:54 | 2020-05-25T17:28:54 | 252,879,077 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 16,150 | r | predict_leafwp_noaddedvars.R | ### Model fitting, Greenhouse experiment 2019
### Goal: Use measured parameters to predict water potential, build a model to fill in
### missing data (so we can treat leaf water potential as a continuous variable)
rm(list=ls())
require(ggplot2)
require(plyr)
require(lubridate)
require(readODS)
require(tidyr)
require(... |
133743d59b722201400677380a16bdda7fb4dbb7 | b0c09959df30b73d953fa98b8bb6c10810fa080d | /man/clr_set_alpha.Rd | b1229e87558047d7eee27a867fea5c7beec09d2c | [] | no_license | k-hench/fftidy | f325ed1aaefb9d0af395ef21acef387849f6a1f1 | a8c2cd364f1597de8612188bbe73cccd7d539d37 | refs/heads/master | 2023-03-15T11:02:11.998683 | 2021-03-05T16:37:54 | 2021-03-05T16:37:54 | 300,317,485 | 0 | 2 | null | null | null | null | UTF-8 | R | false | true | 602 | rd | clr_set_alpha.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sample_colors.R
\docType{data}
\name{clr_set_alpha}
\alias{clr_set_alpha}
\title{The transparent project color scheme}
\format{
An object of class \code{colors} of length 8.
}
\usage{
clr_set_alpha
}
\description{
The transparent project colo... |
c09ae35888889779fb84c0da44255bbce1aa1ba8 | d66dfd6d796d5cec519bdac2a37bbac2d7e8e1a8 | /Prepare_rasters.R | de63a93dd4c24f2332dd79753d5cd71e7bfbd2d2 | [] | no_license | derek-corcoran-barrios/RyeNorskov | 0e9c1ed08bd1ec67531756ff7d110fc199f7c69c | ee84fd3f7c5b76a607be9e4ad2cc4e7ac40c3823 | refs/heads/master | 2023-08-17T05:55:10.860940 | 2021-09-29T06:55:26 | 2021-09-29T06:55:26 | 408,747,301 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,152 | r | Prepare_rasters.R | ## Load packages
library(raster)
library(sf)
## Read in shapefiles to crop and mask
RyeNoskov <- read_sf("ShapeFiles/RyeNoerskov.shp") %>% st_transform(crs = "+proj=utm +zone=32 +ellps=GRS80 +units=m +no_defs")
VegDens <- list.files(path = "O:/Nat_Ecoinformatics-tmp/au634851/dk_lidar_backup_2021-06-28/vegetation_de... |
6d54e5a9913928f92d5f3637748f11d066e4ef3b | c053cc97c204c6af25664cf337d6dd94d984c591 | /tests/testthat/test-validation.R | 0b37314892716108d101a9446060c2544eabe6d1 | [
"MIT"
] | permissive | tidymodels/yardstick | 1b2454ae37da76b6c5c2b36682d573c7044767a7 | e5c36f206fb737fc54b1a6161c09bc0d63b79beb | refs/heads/main | 2023-08-19T03:29:20.953918 | 2023-08-08T21:32:57 | 2023-08-08T21:32:57 | 108,898,402 | 294 | 55 | NOASSERTION | 2023-08-08T21:32:59 | 2017-10-30T19:26:54 | R | UTF-8 | R | false | false | 8,524 | r | test-validation.R | test_that("validate_numeric_truth_numeric_estimate errors as expected", {
expect_no_error(
validate_numeric_truth_numeric_estimate(1:10, 1:10)
)
expect_no_error(
validate_numeric_truth_numeric_estimate(1, 1)
)
expect_no_error(
validate_numeric_truth_numeric_estimate(1L, 1L)
)
expect_no_erro... |
c25a9498d064f32f79e4d5ce04df723c5d4df8b2 | d227e4308a1b139690c7dc89c5cf55ae82e7a44e | /Shiny app/app.R | a9e950e33b3035c23d5f984535e5514ee01806f4 | [] | no_license | PHP-2560/pre-class-work-2018-rsbuckland | 25b4efbe0aeadcb675eefecac6b7ead2e84ed266 | b6e81747598ebf8d600b734acc5686706ee8ebcb | refs/heads/master | 2020-03-29T00:58:23.275128 | 2018-12-05T03:06:43 | 2018-12-05T03:06:43 | 149,365,053 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 411 | r | app.R | library(shiny)
ui <- fluidPage(
titlePanel("Z to P"),
sidebarLayout(
sidebarPanel(
sliderInput("zInput", "Z", 0, 3.4, 0, step = 0.1)
),
mainPanel(
verbatimTextOutput("results")
)
)
)
server <- function(input, output) {
P <- reactive({pnorm(-abs(input$zInput))
})... |
32e306ca41438261a10bb9e050f41b92d97cd8d8 | d1625e2223c81a6c510ccf8bb847c67ed85f8e2f | /tests/testthat/test-anb-families.R | cefff522c8875eca0ed9cab97065330c45f28cb5 | [] | no_license | bmihaljevic/bnclassify | ea548c832272c54d9e98705bfb2c4b054f047cf3 | 0cb091f49ffa840983fb5cba8946e0ffb194297a | refs/heads/master | 2022-12-08T21:37:53.690791 | 2022-11-20T10:00:18 | 2022-11-20T10:00:18 | 37,710,867 | 20 | 12 | null | 2020-08-13T19:39:24 | 2015-06-19T08:30:56 | R | UTF-8 | R | false | false | 4,045 | r | test-anb-families.R | context("Aug nb families")
test_that("graph 2 families nominal", {
g <- test_dag()
f <- graphNEL2families(dag = g, class = 'A')
expect_equal(names(f), c('B', 'A'))
})
test_that("graph 2 families class not in dag ", {
g <- test_dag()
expect_error(graphNEL2families(dag = g, class = 'C'), 'last not f... |
5c5476003edd9e1e2e5809f27d995512377b9d11 | 615f1caa6c4fbabfb82589bc06ba4e6d5b1d72d2 | /R/GenerateSubmission.R | b394d4acec83e85d992578ebf9436ab8b8a00e4b | [] | no_license | tohweizhong/Standard | b60fdfa167aa960aa5390f8d2db78a1c0c952d0b | 661641f66fe8960aa045a959e40c118c40135632 | refs/heads/master | 2020-04-15T06:44:27.164254 | 2016-08-23T06:35:12 | 2016-08-23T06:35:12 | 41,418,868 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 293 | r | GenerateSubmission.R | # Function to generate a submission file for competitions
GenerateSubmission <- function(predictions, filename, samplefilename){
subm <- read.csv(samplefilename)
subm$RESIGNED <- predictions
write.csv(subm, file = paste("submissions/", filename, ".csv", sep = ""), row.names = F)
} |
6df578a21d355b46a679cef59122338a77013414 | 5f98f63fab3cf4480196482b63ae7b023cb22e15 | /parkruns/ui.R | eed9d6f849b30e40585784879d93bd3ce04d9319 | [] | no_license | padpadpadpad/Shiny | 29c160de0a8fa89440602079104d962d1b555d8f | a0573165ce1348b2af775e0009fde94ea27f4dc4 | refs/heads/master | 2021-01-10T06:04:13.486670 | 2017-09-24T14:36:59 | 2017-09-24T14:36:59 | 50,671,806 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,495 | r | ui.R | # shiny app with leaflet to add graphs to the side
# ui
library(leaflet)
library(shinydashboard)
header <- dashboardHeader(
title = "Parkruns UK"
)
body <- dashboardBody(
fluidRow(
column(width = 8,
box(width = NULL, title = 'Introduction',
collapsible = TRUE,
solidH... |
af7822f2b1360ef6e6382c414c0f19d33844ee45 | 7c5caeca7735d7909c29ee3ed6074ad008320cf0 | /man/glomApply.Rd | 082a6090f7226e536ea2334e77132f8e3a04e432 | [] | no_license | ncss-tech/aqp | 8063e800ed55458cfa7e74bc7e2ef60ac3b1e6f5 | c80591ee6fe6f4f08b9ea1a5cd011fc6d02b5c4a | refs/heads/master | 2023-09-02T07:45:34.769566 | 2023-08-31T00:14:22 | 2023-08-31T00:27:14 | 54,595,349 | 47 | 12 | null | 2023-08-17T15:33:59 | 2016-03-23T21:48:50 | R | UTF-8 | R | false | true | 3,696 | rd | glomApply.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/glomApply.R
\name{glomApply}
\alias{glomApply}
\alias{glomApply,SoilProfileCollection-method}
\title{Subset an SPC by applying glom to each profile}
\usage{
glomApply(
object,
.fun = NULL,
truncate = FALSE,
invert = FALSE,
modality ... |
e7893959abe111334e1d70018dded61d3aadfeaf | 8808c17cd8fbf1e484a7da06694622815503f013 | /tests-local/test-local-Gapfill.R | 84f3c61408db3fa7d56796df028f91e43b6c1421 | [] | no_license | florafauna/gapfill | 49002b35a1f498cbeb22f6f78725ab235b32135e | c4a49143605573943a79ebe32a12eae8fc2c5635 | refs/heads/master | 2023-02-28T20:31:14.805035 | 2021-02-11T17:45:06 | 2021-02-11T17:45:06 | 337,828,891 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,056 | r | test-local-Gapfill.R | #require(testthat);
library("gapfill", lib.loc = "../lib")
load("maskstudy.rda")
load("maskstudy_out.rda")
data <- data_array_masked20[1:15,1:15,1:2,1:6]
context("test-local-Gapfill")
test_that("Gapfill-base",{
expect_equal(Gapfill(data = data)$fill, ref)
})
test_that("Gapfill-iMax",{
out <- Gapfill(data = data... |
42109d4004cc604b43b3a07788343b3106974eb5 | 829787776c441d00eb220e907a973a9b066d213b | /R/yaml.R | 09ea9b98db838335dd3244d534c9fb1d09a82bef | [] | no_license | MomX/Momit | 76ab0b1959af5ae11d996e89853175a8e9cedea2 | ead244d7400cae166ece36682185783efd5a5422 | refs/heads/master | 2021-04-28T02:36:02.192219 | 2020-05-08T19:08:17 | 2020-05-08T19:08:17 | 122,117,594 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 746 | r | yaml.R |
# utils ----
#' @export
print.yaml <- function(x, ...){
cat(x)
}
# yaml ----------------------------------------------------
#' yaml wrappers
#'
#' Around `pkg::yaml` base functions
#'
#' @param x any object
#'
#' @examples
#' (chivas$coo[[1]] %>% export_yaml() -> x)
#' x %>% import_yaml()
#' @export
export_yaml <-... |
6c0178341890ee4dfe6ee6d06ed09efe8886e9db | 72d9009d19e92b721d5cc0e8f8045e1145921130 | /rpf/man/rpf.rparam.Rd | b4f3bec16b64bf73ad8dcb81b7c65f4c23471b51 | [] | 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 | true | 929 | rd | rpf.rparam.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/classes.R
\docType{methods}
\name{rpf.rparam}
\alias{rpf.rparam}
\alias{rpf.rparam,rpf.1dim.drm-method}
\alias{rpf.rparam,rpf.mdim.drm-method}
\alias{rpf.rparam,rpf.1dim.graded-method}
\alias{rpf.rparam,rpf.mdim.graded-method}
\alias{rpf.rpar... |
30636adff2c4e9be0c53aaf7ceb0c062c1ffb532 | 13102ffdeb61b0e0be9bd981de725cc836bdd1a8 | /man/downlit-package.Rd | 40dc65e1f6f4382d930d231de1a6ad2dbaf47009 | [
"MIT"
] | permissive | jjallaire/downlit | e057db8b34fcf6b542ebea7470abd75f93a3db20 | 001acfcc71e22e90e2be0ca0291b54fadc5cfc1f | refs/heads/master | 2022-12-16T05:22:55.445421 | 2020-09-18T18:27:46 | 2020-09-18T18:28:03 | 296,702,927 | 1 | 0 | NOASSERTION | 2020-09-18T18:41:15 | 2020-09-18T18:41:14 | null | UTF-8 | R | false | true | 1,821 | rd | downlit-package.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/downlit-package.R
\docType{package}
\name{downlit-package}
\alias{downlit}
\alias{downlit-package}
\title{downlit: Syntax Highlighting and Automatic Linking}
\description{
Syntax highlighting of R code, specifically designed
for the needs... |
29d283489209cd4237acf83a440844acaadc30bb | bb246f2febe8066635a5e3927d4941dd47b45ffe | /Monte Carlo Simulation.R | 79e573f3f6e554ecaccdd816ee8a73158842b74a | [] | no_license | fuatsezer/Simulation | 455f125c3cfa1cbed23f37eb8ee3a11b855d2a26 | cc65f8bf2cd816fa502c4c116a520c5c28db1276 | refs/heads/master | 2022-12-22T15:06:01.985053 | 2020-10-01T09:41:50 | 2020-10-01T09:41:50 | 291,794,980 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 915 | r | Monte Carlo Simulation.R | # Roll d dice; find P(total = k)
probtotk = function(d,k,nreps) {
count = 0
# do the experiment nreps times -- like doing nreps notebook lines
for(rep in 1:nreps){
sum = 0
# roll ddice and find their sum
for (j in 1:d) sum = sum + roll()
if (sum == k) count = count + 1
}
return(count... |
bf1b78026472afebf94f2e29bdce8496a29cb3dc | 7c4ff4c059c519e6c73f19d8023961a02a07899d | /data_management/ui.R | 0ecbf194e773c19692a5c626e24f28153cd14379 | [
"MIT"
] | permissive | bastianilso/data_managementRShiny | 64bdfaf01385f671ea5116791e2f80628558be50 | 1839664ba5ec01e22791f34cecbd87974201f8a2 | refs/heads/main | 2023-03-27T14:38:28.916026 | 2021-03-30T07:31:38 | 2021-03-30T07:31:38 | 319,631,457 | 0 | 0 | MIT | 2020-12-10T13:12:50 | 2020-12-08T12:26:00 | R | UTF-8 | R | false | false | 937 | r | ui.R | #
# This is the user-interface definition of a Shiny web application. You can
# run the application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(shinyjs)
# Define UI for application that draws a histogram
shinyUI(f... |
2e24fc47dd25addab19f9c51370da2ebba5c532b | 7c8b2f9a212192910c6d33e10bc3e92786856f81 | /plot3.R | ac8b66c2e676eccea71d7da27184b8502de8d633 | [] | no_license | Ankit40400/ExData_Plotting1 | 2929cb59f601eee98c94600b87f2c795a4dde735 | 23a8b311afcc138c6ca1236668a304f914bad673 | refs/heads/master | 2022-07-01T17:03:13.206557 | 2020-05-09T12:17:18 | 2020-05-09T12:17:18 | 262,518,085 | 0 | 0 | null | 2020-05-09T07:47:03 | 2020-05-09T07:47:02 | null | UTF-8 | R | false | false | 770 | r | plot3.R | ##loading data
data<- read.csv("./week1assi/household_power_consumption.txt", sep = ";")
## converting date into date format
data$Date <- as.Date(data$Date,"%d/%m/%Y")
data <- data[data$Date == '2007-02-01' | data$Date == '2007-02-02',]
for(i in 3:9) data[,i] <- as.numeric(data[,i])
data$DateTime <- strptime(... |
dc35666b5fa49ff7f94c7ab78f928dc663a1683e | e428691e5a081014ac1c42190249b3a0f04b3de7 | /R/weekRecruit.R | 1ae2bab46b743bd9029f32e7604803fac09228c8 | [] | no_license | maillot-jaune/dashboard | 1b5d6100273cb84cd9272dbbb7180ca0a35fa3a0 | 7460772d4ceed395f5b5f983839f287806fe17b5 | refs/heads/master | 2016-09-10T09:05:35.883996 | 2015-05-13T08:56:27 | 2015-05-13T08:56:43 | 18,711,075 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,228 | r | weekRecruit.R | weekRecruit <- function(){
# library(RMySQL)
sql <- paste(scan('/home/dash/script/select_weekRecruit.SQL',
# sql <- paste(scan('/home/stefan/Desktop/select_weekRecruit.SQL',
what = 'character',
quiet = TRUE),
collapse = ' ')
drv <- dbDriver('MySQL')
con <- dbConnect(drv,
user = 'root',... |
5128b652cc042ad70c54c00fa0e6b2be05f3aea0 | 6805290f5950dadd7bf0df07730fb4a86adda50b | /R/ex101.R | fb84302af135aaac5ee331bd6e84cc0ac0ae4283 | [
"Apache-2.0"
] | permissive | Madonahs/Machine-Learning | e3e6da8ef6344a09b660c3bc9938cd796c636bb7 | 99107b6abf085dfd89376e0777dbd1a9545c9793 | refs/heads/master | 2021-04-09T13:55:13.315482 | 2020-01-22T01:28:47 | 2020-01-22T01:28:47 | 125,732,475 | 44 | 21 | Apache-2.0 | 2019-08-30T19:00:49 | 2018-03-18T14:20:12 | Python | UTF-8 | R | false | false | 380 | r | ex101.R | ---
title: "NN"
author: "Syombua"
date: "April 2, 2018"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
## NN
Multiply $W_1W_2$
$W_1 =\begin{bmatrix} 2 & 0 & 1\\ 0& 1 & 2\\ 3 & 0 & 1\end{bmatrix}$
$W_2 =\begin{bmatrix} 1 & 0 & 1\\ 2& 2 & 1\\ 0 & 3 & 0\end{bmatrix}$
Answer $=\beg... |
c327e081e0677eef69c7f55c9b46c5e78d5378e2 | f4fd87898d4166e51e754512cc7d150400258d79 | /man/data_correct_with_rules.Rd | 623272df5239a46704959e8c595d781b01b943ec | [] | no_license | rte-antares-rpackage/antaDraft | 13a7ea300510fd21058bf349cb9ab32c386616be | 110bd1305a11da0cef8dde5f37f7aa0952ad3882 | refs/heads/master | 2021-09-16T00:11:10.131627 | 2018-06-13T13:24:37 | 2018-06-13T13:24:37 | 94,311,409 | 0 | 0 | null | 2018-06-13T09:06:17 | 2017-06-14T09:03:15 | R | UTF-8 | R | false | true | 847 | rd | data_correct_with_rules.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_correct.R
\name{data_correct_with_rules}
\alias{data_correct_with_rules}
\title{correct datasets}
\usage{
data_correct_with_rules(data, refresh_validation = TRUE)
}
\arguments{
\item{data}{dataset}
\item{refresh_validation}{i... |
aa2e5ee65aa74bea02aff1e9e692b9f199a3a940 | a2e90f6de453a9b346099a8533b8bd10a80005f7 | /functions.R | 8a8d4b157c677b3683d42d8e906590a5df9d5657 | [
"MIT"
] | permissive | songxxiao/txtnb | 5ad940d5e9488743949c9f53f3019b32e96ff946 | 7bc8fcbce4d509b972914c367ea8af5d108de688 | refs/heads/master | 2022-11-14T19:30:40.831882 | 2022-10-12T00:32:17 | 2022-10-12T00:32:17 | 226,848,277 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,388 | r | functions.R | # function define
translation = readRDS("./data/translation.rds")
## translates text into current language
tr = function(text,input){
sapply(text,function(s) translation[[s]][[input$language]], USE.NAMES=F)
}
## predict new string's class using machine learning
## param @model a classification algorithm
## param @s... |
a6ad876d2c6a5af71c0495e5fa8a36d4f22f4f3e | efc5c6096121095cadc37acd42e03fadde89eb06 | /R/model_comparison/models/test_model_cointegration.R | 08f681642e5e0b57a3b971d0e21167a7fe4082a7 | [] | no_license | AlexAfanasev/bookdown_thesis | b04396739f2495dd60a5e5abfeccd916acaf2545 | 1cfe343618b5fca6e53a8c786cb6792589edc0c7 | refs/heads/master | 2023-06-03T11:00:36.998514 | 2021-06-17T16:44:46 | 2021-06-17T16:44:46 | 331,723,414 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,007 | r | test_model_cointegration.R | # SETUP
source(here::here("R", "pd_pomp.R"))
y <- read.csv(here::here("data", "final_dataset.csv"))
source(here::here("R", "covars.R"))
# QUESTION: WHICH MODEL TO CHOSE???
# MODEL 3: MODEL WITH AR AND LAGS & COVARIATES
model_3 <- pomp::pomp(
data = y[, c(1, 2)], times = "time", t0 = 0,
rinit = function(e_lpd_0... |
f35e0a9e37321ab9fe3a64026b1dc56da21d66d3 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/BioGeoBEARS/examples/getAICc.Rd.R | 42c2a18e63dd18ae2ac928dd65f1258c102155c4 | [] | 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 | 422 | r | getAICc.Rd.R | library(BioGeoBEARS)
### Name: getAICc
### Title: Calculate AICc
### Aliases: getAICc
### ** Examples
LnL = -34.5
numparams = 2
samplesize = 20
getAICc(LnL, numparams, samplesize)
LnL = -20.9
numparams = 3
samplesize = 20
getAICc(LnL, numparams, samplesize)
LnL = -34.5
numparams = 2
samplesize = 5
getAICc(LnL, nu... |
1d459a625409da852dd1ba6844fc5afea13e70aa | 34ddd88340d93fc8a674411dfc02340609f3495f | /plot1.R | 1bb2bbcf94009bb4c062d8a9b7491e56f4b920f1 | [] | no_license | khemkaiitr/ExData_Plotting1 | 22e75f2290364d56a1523955e04c7faa93b3f172 | cddd532ba715b941e7b356d53346ed92c9d0e7a1 | refs/heads/master | 2021-01-18T19:51:09.268375 | 2014-09-07T14:25:45 | 2014-09-07T14:25:45 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 496 | r | plot1.R | source('getData.R') #This line gets the data in working directory
data <- data.frame(data)
ndata <- subset(data, as.Date(data$Date, format = '%d/%m/%Y') == '2007-02-01' | as.Date(data$Date, format = '%d/%m/%Y') == '2007-02-02')
# Create the plot
png(file = "plot1.png", bg = "white", width = 480, height = 480)
myplo... |
5a0d0655c29e5e9d11df6db65e04541c1282da52 | d35f7a78d956252e22b0c974acf0dec31dfb7d1a | /man/npmodelcheck.Rd | ff79f08a21ca3dfc019b559ab9da909f5614efab | [] | no_license | cran/NonpModelCheck | 144bc7a51df3a594064f67b0c908e26fff1c3f22 | ee5a3c1664043959b1f3c6207984afb2f8eb0bfb | refs/heads/master | 2021-11-30T08:50:39.002133 | 2021-09-08T12:10:05 | 2021-09-08T12:10:05 | 17,681,163 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,243 | rd | npmodelcheck.Rd | \name{npmodelcheck}
\alias{npmodelcheck}
\title{Hypothesis Testing for Covariate or Group effect in Nonparametric Regression
}
\description{
Tests the significance of a covariate or a group of covariates in a nonparametric regression based on residuals from a local polynomial fit of the remaining covariates using high... |
0e87c596fbba9aa621a8551bbfbc7cb3893096fd | b74b22cb304aeabf341f2c5f4e83427d1318befa | /src/json.montlyedits.R | 1fc3b7b7d889665a0f78dbfcb1d7d07646c25289 | [
"MIT"
] | permissive | OCDX/article-quality | c93d7fdaa00d930ed39538644b0f5b688463e27b | 061c0dea0e6f41a4c4ec9e880fac7dadcae71cda | refs/heads/master | 2020-07-30T16:13:26.317313 | 2018-03-12T16:29:36 | 2018-03-12T16:29:36 | 73,626,777 | 5 | 1 | null | 2017-02-27T00:26:17 | 2016-11-13T16:06:09 | Jupyter Notebook | UTF-8 | R | false | false | 93 | r | json.montlyedits.R | library(rjsonlite)
jsonBoy <- fromJSON("women-scientists-monthly-edits.json", nullValue=NA)
|
ed349004fb126735421422ebbcc49cae316c839a | c220ab52a3f363c3377088e84df41f902d4b5520 | /imputation2/imputeTraits/rareDiseases/export_script.R | 033f3594ccdfa14b774bdeb38d4ff3249cbdc3ca | [
"MIT"
] | permissive | trvinh/genomes-io-prj | 0c00e323d1fb1a28226319c9f98580e820a3dd87 | 6359671245738cfcbfbe88ac9e58a566587d0d3d | refs/heads/master | 2021-07-09T00:46:13.233317 | 2020-11-18T16:21:56 | 2020-11-18T16:21:56 | 213,131,379 | 0 | 2 | MIT | 2020-09-17T18:44:51 | 2019-10-06T08:13:31 | R | UTF-8 | R | false | false | 2,443 | r | export_script.R | export_function <- function (uniqueID, moduleDir, outputDir, gtool) {
if (!file.exists(outputDir)) {
stop(paste("Did not find a output data with this id", uniqueID))
}
table_file <- paste0(moduleDir, "/rareDiseases/SNPs_to_analyze.txt")
request <- table <- read.table(table_file, sep = "\t", hea... |
ed52971dcaf59ba7b2366b13a55b387f9a7bd034 | b8dbee4b91b48121bff4329ce2f37c89d8836290 | /analysis/simulations/simulateTruncatedTranscripts.R | d749fbabb3b7fbec2ac05446cc1082d3ca56b882 | [
"Apache-2.0"
] | permissive | kauralasoo/macrophage-tuQTLs | 18cc359c9052bd0eab45bd27f1c333566fb181d8 | 3ca0b9159f3e5d7d1e0a07cdeadbeb492e361dcb | refs/heads/master | 2021-03-27T19:29:12.456109 | 2019-02-19T13:05:26 | 2019-02-19T13:05:26 | 93,025,290 | 1 | 3 | null | null | null | null | UTF-8 | R | false | false | 9,842 | r | simulateTruncatedTranscripts.R | library("dplyr")
library("BSgenome")
library("devtools")
library("data.table")
library("GenomicRanges")
library("GenomicFeatures")
load_all("../txrevise/")
load_all("../seqUtils/")
library("BSgenome.Hsapiens.NCBI.GRCh38")
#Import transcript annotations
txdb = loadDb("../../annotations/GRCh38/genes/Ensembl_87/Transcri... |
9e37f641cf0445212c0afe158a328a9eb93ea77d | d9e22fee62c67886701ffeaca3b433c8a2d81150 | /score_test_frailty.R | 124f21097a64e1023ce30e918b355543ad7392d7 | [] | no_license | ignareyesa/JMstateModel | 6baeca555e65b61b4564ef8205d09122eb27101b | d11bdc4523f21217cb8ed6def08811171405c62f | refs/heads/main | 2023-03-29T05:35:00.365344 | 2021-03-24T09:39:56 | 2021-03-24T09:39:56 | 351,022,510 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,203 | r | score_test_frailty.R | score_test_frailty <-
function(object)
{
if (object$method != "spline-PH-GH")
stop("Joint multi-state model is only implemented with 'method = spline-PH-GH'")
if(options()$digits < 7)
stop("You have to improve the precision of your machine (with options(digits = k)) or reduce the precision in '... |
f4673f9061a69b196bc2fbf8a744d8003e8e33b3 | 1ce6dbd45ea6d051008b0d1bfaef500aa696cd7e | /R/class_runtime.R | e4a435ecdc43868713ca6b6c45c53b09e2665d5a | [
"MIT"
] | permissive | billdenney/targets | b6515ffd2cbd9c95545385ff6253a2b611c7300e | d881af68925f33283dc4945d9cbc76cd2d5209a9 | refs/heads/main | 2023-08-14T16:59:03.341340 | 2021-09-24T12:44:07 | 2021-09-24T12:44:07 | 406,497,687 | 0 | 0 | NOASSERTION | 2021-09-14T19:32:35 | 2021-09-14T19:32:35 | null | UTF-8 | R | false | false | 2,008 | r | class_runtime.R | runtime_init <- function(
target = NULL,
frames = NULL,
interactive = NULL
) {
runtime_new(
target = target,
frames = frames,
interactive = interactive
)
}
runtime_new <- function(
target = NULL,
frames = NULL,
interactive = NULL
) {
runtime_class$new(
target = target,
frames = fr... |
e8fa86443427e8ca4a918d163536809eac48cfcd | 48d2c8117c4604e32bef0752f16447641bd82718 | /electability/R/TweakAndSummarize.R | f74fbe52b043ae64a80c8600ca7fa21ebf1fb897 | [
"MIT",
"CC-BY-4.0",
"LicenseRef-scancode-public-domain"
] | permissive | tmcintee/electability-2020-pub | b3334cf5ada9c74a43f5cdc9bbb5742cfef290d1 | 5dd97241c7551633890020b4a5ce92eff78dc468 | refs/heads/master | 2020-12-13T09:14:24.949548 | 2020-01-16T17:23:56 | 2020-01-16T17:23:56 | 234,372,855 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,213 | r | TweakAndSummarize.R | TweakAndSummarize <- function(model_sheet,
region_pairs,
candidate_name,
model_name,
region_weight = 0.25,
national_weight = 0.25,
update_we... |
ae61f68be62662cce0b00d0e06577fa0567c610b | 120de1ae49850f8212efc39ab9fa266f175dc4c6 | /man/nameTo.Rd | b4fc72719e3b93d0054965bc9273f77110187361 | [] | no_license | vsrimurthy/EPFR | 168aed47aa2c48c98be82e3d8c833d89e1d11e04 | 544471a8d0cf75c7d65a195b9f6e95d6b1d6800f | refs/heads/master | 2023-08-02T14:50:25.754990 | 2023-07-29T13:56:39 | 2023-07-29T13:56:39 | 118,918,801 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 430 | rd | nameTo.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/EPFR.r
\name{nameTo}
\alias{nameTo}
\title{nameTo}
\usage{
nameTo(x, y)
}
\arguments{
\item{x}{= a logical vector/matrix/dataframe without NA's}
\item{y}{= a logical value, isomekic vector or isomekic isoplatic matrix/df without NA's}
}
\des... |
ab71675a36bf081b3f63dd2e4daa6ea49ab865a6 | dc172ad3471526c167d1d41a97c3ce8d0aa93395 | /man/ce.Rd | 5f37de4f3d7ceffaa3a095881a35c99a796a4414 | [
"MIT"
] | permissive | mcsiple/mmrefpoints | a1140f78d7e8e3819709bde70bbe77ef3e4a30bf | eec714388077c6905bc1c13f0c95ec5f4a5e974b | refs/heads/master | 2023-04-14T07:05:05.067566 | 2022-06-14T05:02:17 | 2022-06-14T05:02:17 | 344,858,328 | 3 | 5 | NOASSERTION | 2022-03-10T23:37:35 | 2021-03-05T15:50:20 | HTML | UTF-8 | R | false | true | 1,731 | rd | ce.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/07_ce.R
\name{ce}
\alias{ce}
\title{Calculate normalized sustainable yield}
\usage{
ce(
S0 = NA,
S1plus = NA,
AgeMat = NA,
nages = NA,
z = NA,
E = NA,
A = NA,
P0 = NA,
N0 = NA
)
}
\arguments{
\item{S0}{Calf/pup survival, a n... |
03673a77c09775f5d0298e96d63a762a2ccb3246 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/reshape/examples/round-any-u2.rd.R | 43de56fe41b5ec9ed15495245dcdd45ed12f310f | [] | 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 | 347 | r | round-any-u2.rd.R | library(reshape)
### Name: round_any
### Title: Round any
### Aliases: round_any
### Keywords: internal
### ** Examples
round_any(135, 10)
round_any(135, 100)
round_any(135, 25)
round_any(135, 10, floor)
round_any(135, 100, floor)
round_any(135, 25, floor)
round_any(135, 10, ceiling)
round_any(135, 100, ceiling)
rou... |
a85560d1f27f9c3d385629474f423da3a2ec8c65 | d5e4d8cc13151bf546727528ccf6849e2b43dc80 | /Assignment 2/R for assignment 2.R | ccf66c341a73e4b8c10805a59f8d7fe307d4ad2f | [] | no_license | jason2133/categorical_data_analysis | d369aeaee5b72cbfeb7da036ce7e413790d9c308 | 2e8bcf90aff80634fcd9ed30674c13f205058396 | refs/heads/master | 2022-01-19T11:43:36.241734 | 2022-01-15T19:02:47 | 2022-01-15T19:02:47 | 175,217,150 | 1 | 0 | null | null | null | null | UHC | R | false | false | 3,377 | r | R for assignment 2.R | # Assignment 2
install.packages("PropCIs")
install.packages("epitools")
install.packages("vcd")
install.packages("vcdExtra")
install.packages("DescTools")
# Print - Table 2.3
table23 <- matrix(c(189, 104, 10845, 10933), ncol = 2)
table23
chisq.test(table23) #Pearson's chi-square test
library(epitools)
riskratio(mat... |
f338880a4d5a7321be714d4dffa9d2539ff61281 | 66e04f24259a07363ad8da7cd47872f75abbaea0 | /Data Visualization with ggplot2 (Part 1)/Chapter 2-Data/2.R | d944bd22b52bd673691dfddacbe8f662c19d1cc2 | [
"MIT"
] | permissive | artileda/Datacamp-Data-Scientist-with-R-2019 | 19d64729a691880228f5a18994ad7b58d3e7b40e | a8b3f8f64cc5756add7ec5cae0e332101cb00bd9 | refs/heads/master | 2022-02-24T04:18:28.860980 | 2019-08-28T04:35:32 | 2019-08-28T04:35:32 | 325,043,594 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,020 | r | 2.R | # base package and ggplot2, part 2 - lm
# If you want to add a linear model to your plot, shown right, you can define it with lm() and then plot the resulting linear model with abline(). However, if you want a model for each subgroup, according to cylinders, then you have a couple of options.
#
# You can subset your d... |
026e7dd13c234f8f46e13810286f02e47da4480d | 7b1c077c809ffdca5b4c199d55dcfab24a8dd59e | /hydroanalyzer/ui.R | 4b3671c3591f8a6c147e91a8227e075659f376bf | [
"MIT"
] | permissive | khaors/binder-hydroanalyzer | 8b7cab50b2c635b321f76d0f34dff054cfeac5c4 | 273bfd9bd1b959f6b496b99ab06e9394933f3851 | refs/heads/main | 2023-03-11T00:25:26.721146 | 2021-03-02T23:56:55 | 2021-03-02T23:56:55 | 343,922,232 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 15,201 | r | ui.R | #
# This is the user-interface definition of a Shiny web application. You can
# run the application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(DT)
# Define UI for application that draws a histogram
shinyUI(pageWi... |
e11333c962e0f71aef85997acec4df7b330ea778 | 7c90bf87ad7974499a5028f268ce735d7fa1e45e | /man/epsilon_dispersion.Rd | 7da67ba6ab106d2eb946c4f32a5e9984aefcdf7c | [] | no_license | ciaranmoore/planar | ee3b4abc56645d1cd36292cb4a0c2abd88c534a0 | d597c58baa3bfdcfeee42c375b5de9e31209a0a0 | refs/heads/master | 2021-01-22T16:13:29.626965 | 2015-04-16T05:14:14 | 2015-04-16T05:14:14 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 540 | rd | epsilon_dispersion.Rd | % Generated by roxygen2 (4.0.0): do not edit by hand
\name{epsilon_dispersion}
\alias{epsilon_dispersion}
\title{epsilon_dispersion}
\usage{
epsilon_dispersion(epsilon, wavelength = seq(400, 1000),
envir = parent.frame())
}
\arguments{
\item{epsilon}{list of real or complex values}
\item{wavelength}{numeric vect... |
cf2a41b2cbe7d8c19f95bf0a9b2154e3b54effb3 | 764560247c3988559ce7bdf8470ab07ac87b3e0e | /man/firstDeriv.Rd | a7ca4be33725f2e313c3ecb80ca71be5d0b8863e | [] | no_license | cran/drsmooth | e563c658f8a915ccf478b4f5b2fddcf366e842f2 | 6bcbd16552a201200fa3c424c296f01b1018d0b4 | refs/heads/master | 2020-12-24T15:49:13.918627 | 2015-09-25T00:01:50 | 2015-09-25T00:01:50 | 17,695,641 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 342 | rd | firstDeriv.Rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/firstDeriv.R
\name{firstDeriv}
\alias{firstDeriv}
\title{First Derivative Function(s)}
\usage{
firstDeriv(mod, n)
}
\arguments{
\item{mod}{The gam model.}
\item{n}{Prediction increments.}
}
\description{
First Derivative Function(s)
... |
c882d216d1a7d6b0427be75d7cc8003bf527102a | b372a5a898a4c9c73566ee38e04d997dc4e0e711 | /R/utilities.R | a826d1eab5096b9719afde4776e239aeddb74106 | [] | no_license | dimbage/epidemia | ccb2b13c25b0dcb8a4857590cf6dc6d2494af3b2 | 0b89f58f39a25dc1b795fea467c54d3e362de3b1 | refs/heads/main | 2023-07-13T08:51:39.922234 | 2020-06-05T17:05:42 | 2020-06-05T17:05:42 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 10,600 | r | utilities.R |
# syntactic sugar for the formula
R <- function(group, date) {}
checkFormula <- function(formula) {
if(!inherits(formula,"formula"))
stop("'formula' must have class formula.", call. = FALSE)
vars <- all.vars(update(formula, ".~0"))
if(length(vars) != 2)
stop("Left hand side of 'formula' must have form '... |
9f4606232426d70bffac4092bc706c70d1ffcc36 | b28f2fa998ce3e1004239aee1f6390dbffcb9ddb | /R/members.R | 1d3b6fba2678d69eed02e56e85b646b11aeed90c | [
"MIT"
] | permissive | linearregression/etseed | cf1a219568bd665cd76e64d77fdaa0218db66a76 | d3c844ae09934efd493fbba2f35a87c3133a495a | refs/heads/master | 2020-12-11T05:45:08.806594 | 2016-07-18T05:40:13 | 2016-07-18T05:40:13 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,003 | r | members.R | #' Manage etcd members
#'
#' @export
#' @name members
#' @param id (character) A member id
#' @param newid (logical) new member id
#' @param ... Further args passed on to \code{\link[httr]{GET}}
#' @return Logical or R list
#' @examples \dontrun{
#' Sys.setenv(ETSEED_USER = "root")
#' Sys.setenv(ETSEED_PWD = "pickbette... |
ca378ed980d5928389ef46f54b2c6d65b6710030 | 3fa1b23746232975b3b014db2f525007a3b49991 | /anna_code/geographic_distribution/plot_v1.R | a5d44cfdafb813ec8c743d9c9b2c52157cc2cf3a | [] | no_license | AshleyLab/myheartcounts | ba879e10abbde085b5c9550f0c13ab3f730d7d03 | 0f80492f7d3fc53d25bdb2c69f14961326450edf | refs/heads/master | 2021-06-17T05:41:58.405061 | 2021-02-28T05:33:08 | 2021-02-28T05:33:08 | 32,551,526 | 7 | 1 | null | 2020-08-17T22:37:43 | 2015-03-19T23:25:01 | OpenEdge ABL | UTF-8 | R | false | false | 884 | r | plot_v1.R | rm(list=ls())
library(ggplot2)
library(fiftystater)
data("fifty_states")
data=read.table("v1.us.broadshare.tally",header=TRUE,sep='\t')
p1=ggplot(data,aes(map_id=State))+
geom_map(aes(fill=Users),map=fifty_states)+
expand_limits(x=fifty_states$long,y=fifty_states$lat)+
coord_map()+
scale_x_continuous(breaks = N... |
c9dc9d6a35c0bf7e24c06ac9dec9baf6c399d17e | 589479cdb8d92cea1734e9787e93e853d9d4cdd7 | /grouping_script.r | 9e757a97059e6c127feeba10a68be51626aa76e5 | [] | no_license | sfatali/Trend-Mining-Exercise | 9ee0b4ac238c458d47445f6a53a9b53a8f17b211 | d62c20dfd67943c97313440a1b12a4e0ee74ad9a | refs/heads/master | 2021-07-21T02:51:20.318085 | 2017-10-31T17:08:53 | 2017-10-31T17:08:53 | 108,731,385 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 13,987 | r | grouping_script.r | grouping = function(text) {
# After working on Scopus:
text <- gsub("open source", "opensource", text)
text <- gsub("internet of things", "iot", text)
text <- gsub("internet things", "iot", text)
text <- gsub("internet things", "iot", text)
text <- gsub("service oriented architecture", "soa", text)
te... |
24fd484af1c92098bb904c9a4f12f7344bd732ad | 9d9cfce0073c28cf3b13050e4a6d3da9354fcf51 | /man/minmaxtemp.Rd | dad9196d55f8bac3f1a49804afd9a2fd71e49a6d | [] | no_license | derekhnguyen/climatePackage_esm262 | cbf77413d32b0c8acde6513fe294418028184f91 | 5e2f4aeee68d89a2f1f330ac71cde44c717a416b | refs/heads/master | 2021-04-16T07:38:06.851749 | 2020-03-26T05:59:33 | 2020-03-26T05:59:33 | 249,338,019 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 533 | rd | minmaxtemp.Rd | % generated roxygen2: do not edit by hand
% Please edit documentation in R/minmaxtemp.R
\name{minmaxtemp}
\alias{minmaxtemp}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Minimum and Maximum Temperature
}
\description{
This function returns min and max temp of a sample df
}
\usage{
minmaxtemp(x... |
688a641c19d97918623fb2d4763d8464f92f903a | ef9acfc3a8166965b7d436e00a162f7a4b723707 | /mineria texto.R | 4b92dd7c1f29108c9c6624e44efdafce98ca863b | [
"MIT"
] | permissive | oddmayo/DS-Training-DAFP | c1b71fd0d4679b4a2dc8c270cbccf9d9f782ed01 | 3980e546b86e5c52797691efce55be6032cefe87 | refs/heads/master | 2022-04-28T17:10:37.342719 | 2019-07-17T23:26:37 | 2019-07-17T23:26:37 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,661 | r | mineria texto.R | # Paquete para leer PDFs no escaneados
library(pdftools)
# Leer CONPES Big Data (subir primero en parte inferior derecha: files, upload)
texto_crudo <- pdf_text("3920.pdf")
# Dejar solo caracteres alfanuméricos
texto_crudo <- gsub(pattern = "[^[:alnum:][:space:]]", " ", texto_crudo)
# Paquete con funciones... |
8a7b32e2e4c127bfa206be84b9b0d07add648df2 | e207c63b517bef7fbc1496f26286e5c5ec811db5 | /churn.r | e901449a32aba63486f05e534907c9d4cf222bdb | [] | no_license | R-Avalos/test_dash | 5866ed792856f7d871bd664959bea74eda647807 | 4c1d90ba88c607ff528160e73d5970ec129ee4f5 | refs/heads/master | 2021-08-23T06:11:40.946400 | 2017-12-03T20:32:17 | 2017-12-03T20:32:17 | 110,893,956 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,030 | r | churn.r | # Churn Data
library(lubridate)
library(dplyr)
library(plotly)
date <- c("2017-1-1", "2017-2-1", "2017-3-1", "2017-4-1", "2017-5-1", "2017-6-1", "2017-7-1", "2017-8-1", "2017-9-1", "2017-10-1", "2017-11-1", "2017-12-1")
total_churn <- c(3, 3, 3.3, 3.2, 3.1, 2.8, 2.9, 3, 2.7, 2.3, 2.8, 2.5)
involuntary_churn <- ... |
8fe78e12a847fbecc7be7b778c131851fd6d219a | fc12495e1457a8154c1ad0e8b439c914c1afca57 | /man/exer_4_13.Rd | 9d0276682557e72879e09087ba5167ecbcf8e40f | [] | no_license | bayesball/tsub | 535c0e85a637c01224a6938fa6699f979e2d54da | 563eded690c2ea219edf213b8611141e8d7a54f7 | refs/heads/master | 2021-01-11T03:19:15.491826 | 2016-10-17T02:09:35 | 2016-10-17T02:09:35 | 71,090,868 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 501 | rd | exer_4_13.Rd | \name{exer_4_13}
\alias{exer_4_13}
\docType{data}
\title{Season batting stats for two players}
\description{
Batting statistics of Jose Altuve and Nelson Cruz for the 2014 baseball season.
}
\usage{
exer_4_13
}
\format{
A data frame.
\describe{
\item{Player}{Player}
\item{AB}{At-bats}
\item{H}{Hits}
\item{X... |
0b7ca5b05c6ebb5b0ac826f756987811d0a1ada3 | b16a5d56c2281543636ddc2b3cd15a61a94de7b0 | /plot/linear_fit.r | 1d7225b8d50e4bd058a2cdf14bdbbc838339b839 | [
"Apache-2.0"
] | permissive | mschubert/ebits | b18bccde6198cb938c04be3704e9fdcff8e5be7d | e65b3941b44174e7267ee142387ffacafca11e53 | refs/heads/master | 2023-07-23T09:09:47.175229 | 2023-07-07T09:36:15 | 2023-07-07T09:36:15 | 18,678,011 | 4 | 2 | null | null | null | null | UTF-8 | R | false | false | 2,513 | r | linear_fit.r | .b = import('../base')
.st = import('../stats')
#.spf = import('../stats/process_formula')
#' Plots a given data.frame as a linear fit with optional subsets
#'
#' @param df data.frame holding at least the columns specified by x, y, and label
#' @param x Column to be plotted on the horizontal axis
#' @pa... |
d275463afba3c2cbe5622b4bb7dd1e7474748206 | 1e09283f2340edc0d7937b42ee4de960d7d0525e | /man/dateForm.Rd | 0431b59322d8753b6e040e12b23eda2edf5cdfca | [
"Apache-2.0"
] | permissive | JDOsborne1/megametadata | a8b2139fdcc5b52788483fcf0cc1fda4b60aabff | 0b5c0e97b499a0f1495a48a05593acbb0fad167f | refs/heads/master | 2020-05-07T13:16:26.670303 | 2020-03-29T16:35:03 | 2020-03-29T16:35:03 | 180,542,223 | 0 | 0 | NOASSERTION | 2020-03-29T16:35:05 | 2019-04-10T08:55:17 | R | UTF-8 | R | false | true | 320 | rd | dateForm.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/meta_extract.R
\name{dateForm}
\alias{dateForm}
\title{Provisional date format checking function}
\usage{
dateForm(vect)
}
\arguments{
\item{vect}{the vector in question}
}
\value{
}
\description{
Provisional date format checking function
}
|
d76ef15efdb13eacc7ebf84daba8f4f94ee31e8d | 671ad9a341b120e24eb1b58313298c004e5a85f5 | /ImportanceSampling/ImportanceSampling.R | c726e7f0d4de72d483a2fad6dce6483781270c06 | [] | no_license | akirahg/CompuStat | 2eae31159f87a5c7b52ede7e1b720ad25e2bacae | aa1e5ada685ef477bbf9f43f7e45cb2c9de5cb52 | refs/heads/master | 2020-12-24T15:40:38.643110 | 2015-10-07T05:31:00 | 2015-10-07T05:31:00 | 42,971,871 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,349 | r | ImportanceSampling.R | # Importance sampling helper script and functions
integrando <- function(x,m=1){
m*exp(-m*x)
}
MethodComparison <- function(nsim, m, a=0, b=2, FUN=integrando, alpha=.05){
quant = qnorm(alpha/2, lower.tail = FALSE)
#Estimación con Uniformes [0.2]
U <- runif(nsim,0,2)
Eval.Unif <- 2*sapply(U,FUN)
Estim.Unif... |
1758fa09f33260e840f3764f414fa58a15e8cb4d | fcc13976b8952fedec00b0c5d4520edc6d5103b9 | /R/multiVCtrl.R | 3a86642804e378dc7fad337b8c75d94074b9a50d | [] | no_license | anngvu/DIVE | 851173b4515ab4fd8c26e171158aa17f079785db | e80d254fc4be2c4a3c12f4a1b4507beff3fe3663 | refs/heads/master | 2023-07-26T00:30:07.924714 | 2021-09-08T15:04:34 | 2021-09-08T15:04:34 | 173,828,093 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 9,358 | r | multiVCtrl.R | #' Shiny module UI for controlling multi-dataset views
#'
#' UI for sourcing and selecting datasets
#'
#' Controls data views geared towards bioinformatics data.
#' Multiple high dimensional datasets can be displayed by calling separate instances of
#' \code{\link{xVUI}} modules, with the contents typically laid out in... |
28362ac7cbe8a01c176fb0e1795282d321e11922 | edb23019571b2e8a8ad92e61eae7e9967d1308ce | /02 Data Wrangling/df_alert_caffeine.R | 23a9dea435f7c01c04ee0a781e2953f53742168a | [] | no_license | andreanc223/DV_FinalProject | 9f35ca246bfb716b2a9aca56d225a9a9ab03f01a | 534f27268631f6d6a25733baa9ca0b51f43419c0 | refs/heads/master | 2016-09-06T01:41:41.609881 | 2015-05-13T19:07:32 | 2015-05-13T19:07:32 | 34,625,773 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,188 | r | df_alert_caffeine.R | library(RCurl)
library(dplyr)
library(tidyr)
library(ggplot2)
library(jsonlite)
require(jsonlite)
df_sleepalert <- data.frame(fromJSON(getURL(URLencode('129.152.144.84:5001/rest/native/?query="select * from tsleepalert"'),httpheader=c(DB='jdbc:oracle:thin:@129.152.144.84:1521:ORCL', USER='C##cs329e_thc359', PASS='orcl... |
3506b3bbd52966c8dbc1bdb2c2f45f4523f70034 | 48b54e972f82a4d37778d0d01320f0198ca45742 | /server.R | 8d9dc325963f3778f1bf0f5683febccce3a0472a | [] | no_license | DrRoad/AMShiny | e2cf59376770c227cbbd61ac3e5ecb41535f3410 | 12ddd667f37bb6238b947d5167d2dfb718a89779 | refs/heads/master | 2020-04-25T13:42:20.146602 | 2018-10-20T19:27:43 | 2018-10-20T19:27:43 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 14,659 | r | server.R |
source('./func/am_helper.R')
source('./func/shiny_helper.R')
my_colors = brewer.pal(6, "Blues")
shinyServer(function(input, output, session){
###############
## Static html pages
###############
output$disclaimer = renderUI(includeHTML("./html/disclaimer.html"))
output$abt = renderUI(includeHTML("./... |
0b2a94ec88846f5a10cf88ab53c7a655aa10b1dd | 438fe09be61cd0be44fa0c0e79073e5d25da4c36 | /man/getStopWordsRatio.Rd | 124504759ac52cc8aad576a53435c77eed18e7ec | [] | no_license | JimSow/textutils | ab545ea0f432fdf5a6bc96a1bd32cfcf335041d0 | 75e438a0c5e748b3a6d0d69d83bcbde1d9456fe6 | refs/heads/master | 2021-01-19T22:47:18.827452 | 2016-03-22T23:00:25 | 2016-03-22T23:00:25 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 409 | rd | getStopWordsRatio.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/text_stats.R
\name{getStopWordsRatio}
\alias{getStopWordsRatio}
\title{Get the ratio of stop words}
\usage{
getStopWordsRatio(string, stpwords)
}
\arguments{
\item{string}{: input string}
\item{output_path}{: path where the output csv file ... |
a61c6d5e9ed03d381c6de2041cdfe36f6f979fe9 | b0f9f9e40ea341b5408664d390700a4062e253be | /man/rquery_prepare.Rd | 26aeb410233545acadbe46761cbfd67952fa13ae | [] | no_license | cran/vtreat | 38fdc9aa43139fbe11e292e26254101af4c2d1a4 | 589514685ca9c4bd92308f8c56a338b8ba510c55 | refs/heads/master | 2023-09-01T16:48:11.190952 | 2023-08-19T20:00:02 | 2023-08-19T21:30:41 | 48,091,035 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,682 | rd | rquery_prepare.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rquery_treatment.R
\name{rquery_prepare}
\alias{rquery_prepare}
\alias{materialize_treated}
\title{Materialize a treated data frame remotely.}
\usage{
rquery_prepare(
db,
rqplan,
data_source,
result_table_name,
...,
extracols = NU... |
696a46a6d74554bceec32df3b97f669e9cd12783 | f5435fd1b9f39bec9b199a573aaf7a5a2de2889f | /man/VarOut-class.Rd | fe4e6eefc564f6d55ba178e340dbe78b38237402 | [] | no_license | brycefrank/spsys | 7977680a1482e294e8316e8c6f3f30124bfa15ab | d88d56661dcf1d6b6b77786a816a27ed1638e099 | refs/heads/master | 2022-12-27T11:41:34.098804 | 2020-07-31T18:02:44 | 2020-07-31T18:02:44 | 257,992,951 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 240 | rd | VarOut-class.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/VarOut.R
\docType{class}
\name{VarOut-class}
\alias{VarOut-class}
\title{Base class for all variance outputs}
\description{
Base class for all variance outputs
}
|
fd251e2cac6b81dfe1719daaf7f646fd0388a205 | de65cc24a284ee7843afee5e7676090b70b0fc3f | /task_9_dataframes.r | c638e5a0ac8b2617e40eca086fe909c2939b4a9d | [] | no_license | Nivas138/LearningRStudio | 101f2c92ebb7255dcdcce2558fb9e197f8ad3ce1 | 9ba1cefdec7f829cbffbd8f7f93c0f72508e7735 | refs/heads/master | 2020-04-18T01:41:34.290516 | 2019-01-24T17:12:04 | 2019-01-24T17:12:04 | 167,129,364 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 719 | r | task_9_dataframes.r | n=c(2,3,5)
s=c("aa","bb","cc")
b=c(TRUE,FALSE,TRUE)
df=data.frame(n,s,b)
df
class(df)
library(help=datasets)
?mtcars #help/desc of car dataset
fix(mtcars) #view the table of dataset
nrow(mtcars) #number of rows
ncol(mtcars) #number of columns
head(mtcars) #top 6 default
head(mtcars,15) #top 15
mtcars[1,2] ... |
7a93b0dafe8e1774e987c2c2671510a61d35686e | 0bdef2bc55eaa8003ba99f9fd5b26eaa675fd2cd | /scripts/extract_megan_annotations.R | 592e9d6b1aedb1483118bf3dd1c92f862e753f54 | [] | no_license | tetukas/ArsM-evolutionary-placements | 465e4abace8e6cdf4f3828b36852ada6e567540e | 749f47814c4cf37766dbfee872c8bd1044548079 | refs/heads/master | 2022-04-15T12:30:57.144225 | 2017-09-08T12:08:27 | 2017-09-08T12:08:27 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,729 | r | extract_megan_annotations.R | #!/usr/bin/env Rscript
# This script help to extract for each read the full taxonomic path of MEGAN LCA annotations
# The input file must be created by copying-pasting the Inspector windows, after uncollapsing each taxonomic node.
# This script uses a function than retrieve the full taxonomic path from NCBI from any t... |
b2a8b2334c5006b0ba9e39d2adc73eb1a400e8fb | e44f7c7c1cbcd8aa198bd61439807d7c1ff2d706 | /plot4.R | 5c9ad364d755f93aa398a54381117d9781baed99 | [] | no_license | pepcarrera/ExData_Plotting1 | 7ef3bfbd25453173a6ec5256409de643038b28c0 | 1cbd922bc4af1f65d9bdc01204d09456f5e2b14c | refs/heads/master | 2021-01-16T19:38:23.343711 | 2014-07-08T03:09:06 | 2014-07-08T03:09:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,085 | r | plot4.R |
##Load Data from Data set
##Set ? entries as NA while using ; as seperator for the data
elecData <- read.table("household_power_consumption.txt",
header=TRUE, sep=";", na.strings="?")
##Set ? Convert Date column in data set to date format
elecData$Date <-as.Date(elecData$Date, format="%d/%m/... |
f8ff07bcf7d182d42e726c81cfd894612341f27c | ce6c631c021813b99eacddec65155777ca125703 | /R/rbindQW.R | 23a38407af0b6034f898ad09f3f8102a121f3b9a | [
"LicenseRef-scancode-warranty-disclaimer",
"LicenseRef-scancode-public-domain-disclaimer"
] | permissive | Zhenglei-BCS/smwrQW | fdae2b1cf65854ca2af9cd9917b89790287e3eb6 | 9a5020aa3a5762025fa651517dbd05566a09c280 | refs/heads/master | 2023-09-03T04:04:55.153230 | 2020-05-24T15:57:06 | 2020-05-24T15:57:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,282 | r | rbindQW.R | #' Combine Data by Rows
#'
#' Combines a sequence of data frame arguments and combine by rows. This is a
#'specialized version of rbind that works for data frames that contain columns
#'of class "qw."
#'
#' @param \dots any number of data frames with identical columns. The missing value \code{NA}
#'is permitted as a ... |
4bb0dbd6ecde9ec48809d914c99ba382312bf4c3 | c85471f60e9d5c462de6c60c880d05898ec81411 | /cache/Z3tt|TidyTuesday|R__2019_27_Franchise.R | 0ab27569b3aca4e08f921506e45379275f9118b2 | [
"CC-BY-4.0",
"MIT"
] | permissive | a-rosenberg/github-content-scraper | 2416d644ea58403beacba33349ee127e4eb42afe | ed3340610a20bb3bd569f5e19db56008365e7ffa | refs/heads/master | 2020-09-06T08:34:58.186945 | 2019-11-15T05:14:37 | 2019-11-15T05:14:37 | 220,376,154 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 9,449 | r | Z3tt|TidyTuesday|R__2019_27_Franchise.R | ## ----setup, include=FALSE------------------------------------------------
knitr::opts_chunk$set(echo = TRUE, warning=FALSE)
## ----prep, message=FALSE-------------------------------------------------
## packages
library(tidyverse)
library(patchwork)
library(tvthemes)
## ggplot theme updates
source(here::here("them... |
8ef3f8219be36d91851d68cd056e524c214b8788 | 9895ab0556ce062451b44520b98300d501e9176a | /scripts/Section 4 - Matrices/MatrixOperations.R | 01b8b234becc56c31a67c0e8a2f37e563c64789c | [
"MIT"
] | permissive | LEMSantos/udemy-R_programming_A_to_Z | 8359c9fab7def1e9743f01c254f7ab5d3d697b12 | 7319f9288489a9a619f1fffb0cf2016875752008 | refs/heads/main | 2023-04-04T18:53:47.836423 | 2021-04-18T14:59:29 | 2021-04-18T14:59:29 | 349,807,412 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 231 | r | MatrixOperations.R | library(here)
source(here::here('scripts', 'Section 4 - Matrices', 's4-BasketballData.R'))
Games
rownames(Games)
colnames(Games)
Games['LeBronJames', '2012']
FieldGoals
round(FieldGoals / Games, 1)
round(MinutesPlayed / Games)
|
e8d02d347c9c5c131efb9a0010614e54b333fb73 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/mlogit/examples/scoretest.Rd.R | d67a712c82c6ddab680f914eb6b65430fc7f1476 | [] | 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 | 652 | r | scoretest.Rd.R | library(mlogit)
### Name: scoretest
### Title: The three tests for mlogit models
### Aliases: scoretest scoretest.mlogit scoretest.default waldtest.mlogit
### waldtest lrtest.mlogit lrtest
### Keywords: htest
### ** Examples
library("mlogit")
data("TravelMode", package = "AER")
ml <- mlogit(choice ~ wait + travel... |
da20b72d68d88af038aed6987d6472ba43cb3657 | 55e51b89b134522678d1f58d3006a5e37d1e7462 | /man/z3_personf.Rd | d1b0ff05cb0eb64537eb555b862807eb39a9848b | [] | no_license | cran/IRTpp | 49da8ebb3f62625634aee44e3b0d4568b9d250a0 | 3cdd14c81e00802d2f1bcd022eebcc403c636798 | refs/heads/master | 2021-01-15T15:25:21.955389 | 2016-07-05T14:02:36 | 2016-07-05T14:02:36 | 54,411,939 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,350 | rd | z3_personf.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/itemfit.R
\name{z3_personf}
\alias{z3_personf}
\title{Z3 Person fit statistic}
\usage{
z3_personf(data, zita, patterns)
}
\arguments{
\item{data}{a data frame or a matrix with the test.}
\item{zita}{a list of estimations of the pa... |
c92aa34be8ab10216ebde4ae7734ba568e32ae32 | 46b5ab567c4f63bb764972c52a407ce2db9788d4 | /man/vertlocations.Rd | b78af42d5f1147ed0f8018f07e529721f557d724 | [] | no_license | jotegui/rvertnet | 078de18438f050c0ba4a4bec514cf9f9d83f3a08 | 516937fa762173c3b09433d9e3a054b6c206d910 | refs/heads/master | 2021-01-17T23:14:01.187716 | 2012-09-21T05:38:13 | 2012-09-21T05:38:13 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,596 | rd | vertlocations.Rd | \name{vertlocations}
\alias{vertlocations}
\title{Retrieve locations and number of occurrence records for an organism from VertNet v2 portals.}
\usage{
vertlocations(key = "r_B68F3", grp = "fish", t = NULL,
l = NULL, c = NULL, d = NULL, q = NULL, p = NULL,
m = NULL, url = NULL)
}
\arguments{
\item{key}{API ... |
1bc12e396b4aee739d62e8b1d5e79a33e0e53a2e | cfb5af31d5105a6b6d81adf6221ecca7e572b8c8 | /cachematrix.R | 3feb1b359285af408deeda374ee08c3e3ed01ef0 | [] | no_license | abie/ProgrammingAssignment2 | ba120e34ee1b273da673ed77f9a05e9c31bf7bed | 557344472361e6b775bbbfcb39baa0ce19accc05 | refs/heads/master | 2021-01-18T02:07:11.045362 | 2015-07-26T19:52:03 | 2015-07-26T19:52:03 | 38,132,763 | 0 | 0 | null | 2015-06-26T20:43:07 | 2015-06-26T20:43:03 | null | UTF-8 | R | false | false | 773 | r | cachematrix.R | ## This function creates a special "matrix" object that can cache its inverse.
makeCacheMatrix <- function(x = matrix()) {
im <- NULL
set <- function(y) {
x <<- y
im <<- NULL
}
get <- function() x
setinverse <- function(inverse) im <<- inverse
getinverse <- function() im
list(set=set, get=get, setinverse=set... |
ed32c47b738c4d1817cc3306d48ab84759a4fc19 | 0be1777c9406537edabcc90a704b3bd6687bb19b | /R/4-16.R | 2cfcb10c292d011e314c3d0e4360c54c0ab8aa06 | [] | no_license | mitchellchris/stats-notes | b53b9a50423352df44269241e286f528d5e15ab4 | 05d00deb57e4627587b5b57bab29b3bf8590ab8e | refs/heads/master | 2020-04-07T11:21:42.069781 | 2014-04-29T14:58:03 | 2014-04-29T14:58:03 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,678 | r | 4-16.R | # 3 ways to bootstrap (sample with replacement)
# 1) for loop
# 2) boot package
# 3) replicate() function
# 7: Pop with normal dist mean = 36, sd = 8.
set.seed(13)
rs <- rnorm(200, 36, 8) # 200 samples from normal dist with mean=36 and sd=8
DF <- data.frame(x = rs)
# density plot
p1 <- ggplot(data=DF, aes(x=x)) + g... |
6855c0ea044b1fbb56d5836911fbaeba73010c7f | b459f6b664c6b0bb693554a7a5e05413da311390 | /02_nyc_squirrels_by_color.R | 7a386ab00db20837fefed25689dc43509e5ca19d | [] | no_license | denisevitoriano/Tidytuesday | c7dc7366e36514f2bf8c8827da6b580e26652eaa | e099ef7b2e1640285f75ce2376ebc0e7cfc338ed | refs/heads/master | 2020-09-04T04:47:15.278256 | 2019-11-06T20:33:32 | 2019-11-06T20:33:32 | 219,661,079 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 846 | r | 02_nyc_squirrels_by_color.R | library(tidyverse)
theme_set(theme_light())
nyc_squirrels <- readr::read_csv("https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2019/2019-10-29/nyc_squirrels.csv")
# By hectare
nyc_squirrels %>%
count(hectare, sort = FALSE)
by_hectare <- nyc_squirrels %>%
group_by(hectare, primary_fur... |
b62e822dd622e373214937460ef72e2c0f8c2975 | 5ec2fa5348d50157287668785946117ba553b4a4 | /scripts/01_plot_fiscal_note_fiscal_solvency_data.R | 7aae9f690558b59d46f6c62f9149736fc645da1f | [
"CC-BY-4.0"
] | permissive | RobWiederstein/fiscal_notes | c615534eee52129ea79c2662ed01667d4eb277dd | 86f87c60db7fe4f75b340e7b80346b310dae4d50 | refs/heads/master | 2020-04-20T10:21:09.071134 | 2019-10-03T11:32:07 | 2019-10-03T11:32:07 | 168,788,332 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,864 | r | 01_plot_fiscal_note_fiscal_solvency_data.R | ## Rob Wiederstein
## rob@robwiederstein.org
## explore correlation between
## fiscal notes and fiscal soundness
###############################################################################
#read in cbpp better cost estimates data
file <- "./data/tabula-2015-11-24_cbpp_better_cost_estimates_table1.csv"
df <- r... |
b316c23d6a2c6f8b49d2839516b3e499c31bc0db | 1542b8ef5c6387facf4d49f8fd4f6b5ef5d8e9c0 | /R/xRWkernel.r | c10f8a39ecb0ab7fbedf4e9ce063ecc55be53d08 | [] | no_license | wuwill/XGR | 7e7486614334b664a05e389cd646678c51d1e557 | c52f9f1388ba8295257f0412c9eee9b7797c2029 | refs/heads/master | 2020-04-12T12:38:04.470630 | 2018-12-19T17:40:30 | 2018-12-19T17:40:30 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,494 | r | xRWkernel.r | #' Function to calculate random walk kernel on the input graph solved analytically
#'
#' \code{xRWkernel} is supposed to calculate a weighted random walk kernel (at a predefined number of steps) for estimating pairwise affinity between nodes.
#'
#' @param g an object of class "igraph" or "graphNEL". It will be a weight... |
cccb695048d10a288fe74a878bc2f740a68f1bbe | 401d48b917525346b9b4320607ebb4a7df373d8a | /R/tidal_codes.R | a2762c5128640aa9c4a2400c89185cb6070f6bea | [] | no_license | CamiloCarneiro/eneRgetics | 0f7822f027320dbf2c04eb046d1a4e3d00062c3e | 0910832fd62330dbc11022b3206c19c1670d6158 | refs/heads/master | 2023-04-27T11:37:20.387666 | 2023-04-14T07:33:55 | 2023-04-14T07:33:55 | 202,355,162 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,586 | r | tidal_codes.R | #' Creates tidal codes
#'
#' Creates a numerical code for the tide state in relation to the closest low
#' tide peak.
#'
#' For each observation, the time difference to the nearest low tide is
#' calculated (in hours) and coded into a numerical category where 0
#' represents low tide and 6 high tide. If tide is ... |
9ba0c56c14b94926cd4b873462ddee9ce9b7055f | 8c20cb1afd621c732382ffe50a53b1a978010a42 | /R/plotSimulation.R | 4506e401f62e2138bc18f793c6f52054fda0b270 | [] | no_license | BlasBenito/virtualPollen | 01daa3bec05c5caeefa2f52109df8a7df115c0d0 | b33c7929ce802f3764fdcee39a911243984698ee | refs/heads/master | 2022-02-28T17:42:46.520588 | 2022-02-11T17:46:27 | 2022-02-11T17:46:27 | 177,762,046 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 10,125 | r | plotSimulation.R | #' Plots results of \code{\link{simulatePopulation}}.
#'
#' @description This function takes as input the output of \code{\link{simulatePopulation}}, and plots the pollen abundance, number of individuals, biomass, driver, and environmnetal suitability of each simulation outcome.
#'
#'
#' @usage plotSimulation(
#' sim... |
ddefb43ab7860b30d1cf489ac0ead1c4cd10898e | 0a9fa200d07db384931ccd5b517eb26d09d89e8b | /man/Approximator.Rd | daa5d44a2520f5e391758965db49edf57dda9c33 | [] | no_license | Alexandra930/PhyInformR | 6b87d2f96275a3b150d0b5c7ad5c5f2c6ecedd8a | c111e7478123ab872842e1d29d7586ac3c74dc5f | refs/heads/master | 2022-03-16T14:15:35.694345 | 2016-11-15T14:59:44 | 2016-11-15T14:59:44 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,271 | rd | Approximator.Rd | \name{Approximator}
\alias{Approximator}
\title{Quantify Quartet Resolution Probabilities Using 2012 Formulation}
\description{
Quantify QIRP, QIHP, or QIPP using the equations from Townsend et al. 2012.
%% ~~ A concise (1-5 lines) description of what the function does. ~~
}
\usage{
Approximator(t, t0, rateVector, ... |
9131d1e02c9f00e3ad9687c6637235c2e9639365 | 5822a9f99a63bc7f0f50ac89e67b4be7f8b7e35e | /modules/c_variables/wood_c_pool/make_wood_table.R | 17f0f1d3ac0060c0a5e1572aa3b32f2725b8a079 | [] | no_license | mingkaijiang/EucFACE_modeling_2020_site_parameters | 845362edcc0867d5becb3730305f08ddc7744b80 | 734c09a9f88b649b2300ac876bd70433839a5816 | refs/heads/master | 2021-04-16T01:20:29.998190 | 2020-03-24T04:49:25 | 2020-03-24T04:49:25 | 249,315,857 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,418 | r | make_wood_table.R |
# Make the live wood C pool
make_wood_table <- function(ring_area){
#### download the data from HIEv
download_diameter_data()
#### read in 2012-15 data sets
f13 <- read.csv(file.path(getToPath(), "FACE_P0025_RA_TREEMEAS_2012-13_RAW-V1.csv"))
f14 <- read.csv(file.path(getToPath(), "FACE_P0... |
cab0a203f29ee0696c967b758f3e8eed3741dfc1 | 4f6fa43be679bed6016351f81dae8d642ca8b93e | /R/compat-dplyr.R | 735d259fdff272af4f348566e4614e9be6318d51 | [] | no_license | DavisVaughan/strapgod | 9c0442b5b79d0bd47c2bfc2acaa01f4272706dff | ea2b1ecfc780a44ffa934c9bc7c2032954f4ffaa | refs/heads/master | 2021-08-15T04:54:51.408714 | 2020-01-20T13:37:45 | 2020-01-20T13:37:45 | 149,317,827 | 67 | 7 | null | 2021-08-09T17:52:05 | 2018-09-18T16:18:02 | R | UTF-8 | R | false | false | 6,049 | r | compat-dplyr.R | # ------------------------------------------------------------------------------
# Interesting dplyr functions
# summarise()
# do()
# ungroup()
# group_nest()
# group_map()
# group_modify()
# group_walk()
# group_split()
# group_keys()
# group_indices()
# In theory we could let the default `summarise()` do its thing.... |
1cde74b36cd7f8b56601929c9294f8badb59ad7f | 4fed9d47a2af0bd99de61068b7ab54f08b109ebd | /Rmetapop/man/LVBweight.Rd | 64092eba4f3d89af88747324e5a3b657969058bb | [] | no_license | dkokamoto/Rmetapop | 402d5dde93b103df757d54e1852ce20e61c490f1 | 281c1fbf4c233c1504ba0c116ffbbff9836cf351 | refs/heads/master | 2022-10-12T14:55:11.954234 | 2018-05-28T18:48:43 | 2018-05-28T18:48:43 | 38,710,185 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 326 | rd | LVBweight.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ancillary.R
\name{LVBweight}
\alias{LVBweight}
\title{Weight at age using the LVB growth equation and length-weight relationship.}
\usage{
LVBweight(age)
}
\description{
Weight at age using the LVB growth equation and length-weight relationsh... |
100acaf5fba874cee6ced05c7a4157be1aec6099 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/SpatialTools/examples/dist2.Rd.R | 98f52957bc553c30c2a94b40cdfd8f2f99a11590 | [] | 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 | 251 | r | dist2.Rd.R | library(SpatialTools)
### Name: dist2
### Title: Calculate Euclidean distance matrix between coordinates of two
### matrices
### Aliases: dist2
### ** Examples
x1 <- matrix(rnorm(30), ncol = 3)
x2 <- matrix(rnorm(60), ncol = 3)
dist2(x1, x2)
|
d26d3d6ec52a10a842bc40785c2394810393c2f1 | f3824adc3a9a5865b6d6cf78641fdda1db7598a1 | /man/priorityqueue.Rd | 9951f2c6e2402bee78f1f4ba4d88aa4bdffb0b26 | [
"MIT"
] | permissive | n8epi/gmRa | 31f3d3f99e74af0eee054fa8b743100354c0a3d1 | 29764e76b65482e7663915d6ee403cc94d5620d3 | refs/heads/master | 2021-01-10T06:52:47.200002 | 2016-09-27T19:37:49 | 2016-09-27T19:37:49 | 54,762,691 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 250 | rd | priorityqueue.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_structures.R
\name{priorityqueue}
\alias{priorityqueue}
\title{Priority Queue data structure}
\usage{
priorityqueue()
}
\description{
Priority Queue data structure
}
|
a5d7bcf55c9474889e693cb84aa862e78049dd74 | 1ac8617d2cc54b131798b7ffb8eb3ad81059010c | /Sentiment Analysis Using R/ui.R | 9cdc7db7a336c8449d0228254cdaff186b41affd | [] | no_license | paonikar/Sentiment-analysis-R- | 5ffea59251144dde4ee716c38f83f955bf7b134d | eab4d5f6ec5c2827bbcd6e3623b05d115ae8699c | refs/heads/master | 2020-12-04T05:01:54.258414 | 2020-01-03T16:27:53 | 2020-01-03T16:27:53 | 231,622,980 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,611 | r | ui.R |
library(shiny)
shinyUI(pageWithSidebar(
headerPanel("Sentiment Analysis Using R"),
# Getting User Inputs
sidebarPanel(textInput("searchTerm", "Enter data to be searched with '#'", "#"),
sliderInput("maxTweets","Set the number of recent tweets to be used for analysis:",min=5,max=1000,value=500),
subm... |
2398c7780a2aea98ecd2e7c7c3093880f86634de | 4c50e336c95095ce3fac4e6333fc3a83db35dbc6 | /R/CCAMLRGIS.R | c7bca2db38018221c1a223bcaeeb68b9355b808a | [] | no_license | rsbivand/CCAMLRGIS | ee0a55cda86401d7904f86b03ee8c8b27f3c2006 | 8fd07db6efbab3983deeb5ebf260afb80be62782 | refs/heads/master | 2020-11-26T09:25:29.588205 | 2020-05-25T10:38:54 | 2020-05-25T10:38:54 | 229,028,616 | 0 | 0 | null | 2019-12-19T10:14:41 | 2019-12-19T10:14:40 | null | UTF-8 | R | false | false | 2,012 | r | CCAMLRGIS.R | utils::globalVariables(c('CCAMLRp','Coast','Depth_cols','Depth_cuts','Depth_cols2','Depth_cuts2',
'GridData','Labels','LineData','PointData','PolyData','SmallBathy','ID'))
#'
#' Loads and creates spatial data, including layers and tools that are relevant to CCAMLR activities.
#'
#' This package provides two broad cate... |
20a78b953f494128060025a4afe66825c6482831 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/palasso/examples/dot-cv.Rd.R | 64269f1331fe8b89a3a726e54714765666abedc9 | [] | 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 | 103 | r | dot-cv.Rd.R | library(palasso)
### Name: .cv
### Title: Cross-validation
### Aliases: .cv
### ** Examples
NA
|
46dd051fd04530bad14ec5cad314e65a3fece2d1 | 021498dd1ed1eb755575e7dfbc8b8f9fae927831 | /man/ISOCitation.Rd | 2fa6f246b3cf0915947ab7a6dd269fa0b52d8df6 | [] | no_license | 65MO/geometa | f75fb2903a4f3633a5fcdd4259fd99f903189459 | c49579eb5b2b994c234d19c3a30c5dad9bb25303 | refs/heads/master | 2020-04-08T12:22:44.690962 | 2018-11-22T22:51:57 | 2018-11-22T22:51:57 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,598 | rd | ISOCitation.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ISOCitation.R
\docType{class}
\name{ISOCitation}
\alias{ISOCitation}
\title{ISOCitation}
\format{\code{\link{R6Class}} object.}
\usage{
ISOCitation
}
\value{
Object of \code{\link{R6Class}} for modelling an ISO Citation
}
\description{
ISOCit... |
82b34ea8535ae4837a2bfd747da4a2f5f634088f | c98f1fae6230551046ed2ddee74fa64a267509d2 | /R/aws.R | 8941ddbb5933247076d7261840b6faa27ae46eae | [] | no_license | datacamp/r-package-parser | 21a870b4af8725347bd499fbf7ac7dcb5de8b7d8 | 63e0062d0cb53a9fd325f24b8264c6891d1a3d06 | refs/heads/master | 2022-08-27T14:41:24.409045 | 2022-08-15T14:29:31 | 2022-08-15T14:29:31 | 81,352,913 | 2 | 2 | null | 2022-08-15T14:29:32 | 2017-02-08T16:54:11 | R | UTF-8 | R | false | false | 3,302 | r | aws.R | #' @importFrom jsonlite write_json
dump_jsons_on_s3 <- function(description, topics) {
pkg_name <- description$Package
pkg_version <- description$Version
local <- file.path(getwd(), pkg_name, pkg_version)
remote <- file.path("s3://assets.rdocumentation.org/rpackages/unarchived", pkg_name, pkg_version)
dir.cr... |
76e61bca7a86b4fe6b3c07e3ff5e462e0e6b6056 | 60d17a32a7717f2ef63ad305137e491c8dbcd558 | /R/classes.R | 066c9b74030774d379bb107656274e4f015018c9 | [] | no_license | benstory/mitoClone2 | d08e10575f82a375d1ef01844a0500adcf750b8b | aa8ef170defb943f2eeec4993a5fe9955c1381c7 | refs/heads/main | 2023-06-20T13:45:55.555113 | 2023-06-16T06:22:04 | 2023-06-16T06:22:04 | 378,751,189 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 10,997 | r | classes.R | #'mutationCalls class
#'
#'To create this class from a list of bam files (where each bam file corresponds
#'to a single cell), use \code{\link{mutationCallsFromCohort}} or
#'\code{\link{mutationCallsFromExclusionlist}}. To create this class if you
#'already have the matrices of mutation counts, use its contstructor, i.... |
0195bb2fdc226fa9022c38a446d1a1ef37be53a2 | f56e47d46acb433fb720c3b57e5889ba761873f9 | /data_france/Roadmap.R | 581854647bb16444c699a2e15b94742b52433324 | [] | no_license | matthiasmace/coronavirus | b97b84c7280e8ff200000be6a7e7d96ee105b00b | aa5a344488f7bdd5ce48d18b061d5c3c8ecae898 | refs/heads/master | 2021-04-21T15:57:18.426905 | 2020-11-26T13:20:16 | 2020-11-26T13:20:16 | 249,794,137 | 0 | 0 | null | 2020-03-24T19:04:02 | 2020-03-24T19:04:00 | null | UTF-8 | R | false | false | 8,574 | r | Roadmap.R | ## data France
, fluidRow(
column(12,
h1("CovId-19 for People", align="center")
, h2("SARS-CoV-2 pandemics data display & analysis Webpage for the people", align="center")
, p("Données Source",
a("INSEE ???",
href="https://ourworldindata.org/coronavirus"),
"| Link to the dataset ... |
70a1ea65d77240163ae85e563e6863f5b3e0de22 | cff3dad31f34070a0459506762e97accba287fad | /Pmetrics/R/makePTA.R | e62ef4032b5f88f2284cc43be774adfe951d958b | [] | no_license | nickibeaks/Pmetrics | 0264959e0f4a6281a4e5e1ec43934be481ffb4f8 | 1d10559c754e6a5bd85cda749fc4fda5045dc606 | refs/heads/master | 2020-05-29T12:24:45.659832 | 2014-07-23T18:33:41 | 2014-07-23T18:33:41 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,485 | r | makePTA.R | #' Calculates the Percent Target Attainment (PTA)
#'
#' \code{makePTA} will calculate the PTA for any number of simulations, targets and definitions of success.
#' Simulations typically differ by dose, but may differ by other features such as children vs. adults.
#'
#' @title Calculation of PTAs
#' @param simdata A vec... |
fe8fb1e714093b0af43cfa567122d818500a74a1 | 958717071388748f12f69d7015cee40adf1dca83 | /plot4.R | 2b547388325467131c492c1d1fa634e6df1cc2e3 | [] | no_license | srishtigarg3/exploratory-data-analysis | 8e5f15629a7e2ee7f25d95c30ed864a053bd1ce3 | 0f3d4364270981e5fc12f11e4569ac0556ab485e | refs/heads/master | 2020-06-30T23:46:36.736428 | 2016-11-23T09:37:10 | 2016-11-23T09:37:10 | 74,561,625 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,045 | r | plot4.R | data <- read.table("C:/Users/Srishti/Desktop/household_power_consumption.txt", header=TRUE, sep=";", stringsAsFactors=FALSE, dec=".")
subdata <- data[data$Date %in% c("1/2/2007","2/2/2007") ,]
globalap <- as.numeric(subdata$Global_active_power)
datetime <- strptime(paste(subdata$Date, subdata$Time, sep=" "), "%d/%m/... |
4fad96ef622347d200df63680892cfefb38a2420 | ef4eb23543224c14f4cae67190d1f82bd881a4a4 | /dfg_for_kilimanjaro/ndvi_kilimanjaro/src/gimms/gimmsNdviHarmonics.R | f5f00e5a11b27eec433e822682b87619250cf048 | [] | no_license | environmentalinformatics-marburg/magic | 33ed410de55a1ba6ff943090207b99b1a852a3ef | b45cf66f0f9aa94c7f11e84d2c559040be0a1cfb | refs/heads/master | 2022-05-27T06:40:23.443801 | 2022-05-05T12:55:28 | 2022-05-05T12:55:28 | 9,035,494 | 6 | 7 | null | null | null | null | UTF-8 | R | false | false | 8,106 | r | gimmsNdviHarmonics.R | # # Working directory
# switch(Sys.info()[["sysname"]],
# "Linux" = {path.wd <- "/media/envin/XChange/kilimanjaro/ndvi"},
# "Windows" = {path.wd <- "D:/kilimanjaro/ndvi"})
# setwd(path.wd)
# Packages and functions
lib <- c("raster", "rgdal", "TSA", "RColorBrewer")
sapply(lib, function(...) require(...,... |
934adf374b741d8505cad8433e09db094c4ba47c | fbd1b4d98cad1db8c1aefbd55d16bf8dc3cd18c1 | /plot2.R | 8dd16aa39ce4de17329f4e63bd40e9c2aea28c79 | [] | no_license | adtai/ExData_Plotting1 | c389a57eee27b04f5063e1d2127d3c65a7927e64 | 8403190efe12ae2f808c66c4612b1236ed04bba9 | refs/heads/master | 2020-05-19T16:35:36.718743 | 2015-04-12T02:09:40 | 2015-04-12T02:09:40 | 33,796,339 | 0 | 0 | null | 2015-04-11T23:32:18 | 2015-04-11T23:32:18 | null | UTF-8 | R | false | false | 1,194 | r | plot2.R | library(lubridate)
# Load the data file
# fileUrl <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
fileUrl <- "http://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
# Go from zip file to txt
# http://stackoverflow.com/questions/3053833/using-r-... |
542dbe325baf834b2719cf604a4e1417f5a3ddf4 | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /cran/paws.internet.of.things/man/iot1clickprojects_delete_placement.Rd | 7c45e2659261739214ff09a555a79577ee642fea | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | true | 819 | rd | iot1clickprojects_delete_placement.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/iot1clickprojects_operations.R
\name{iot1clickprojects_delete_placement}
\alias{iot1clickprojects_delete_placement}
\title{Deletes a placement}
\usage{
iot1clickprojects_delete_placement(placementName, projectName)
}
\arguments{
\item{placeme... |
f4d46c75ecb279aaab9ca5a9bc4f5bf7304ac328 | 873f2f21ba9477f77fbd63471f68fb74f0096fa7 | /global.R | 0cb6de84d2ecee392a15b88e407bbe1841b3712b | [] | no_license | cashoes/shinyDIABLO | 9724036ecbc28bf0944873cec712e5cdce90b1aa | 6849c1dffa10db61f497ed8b94aeba85dc2ce4dd | refs/heads/master | 2021-09-06T00:15:44.371020 | 2018-01-31T22:21:46 | 2018-01-31T22:21:46 | 119,751,598 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 786 | r | global.R | # Define globally available objects
# imports -----------------------------------------------------------------
library(shiny)
library(shinycssloaders)
library(shinyBS)
library(shinydashboard)
library(shinythemes)
library(plotly)
library(network)
library(sna)
library(igraph)
library(intergraph)
library(visNetwork)
... |
d803b3e57c4c5f3a756a79abb26f50673ac9a86d | 7a95abd73d1ab9826e7f2bd7762f31c98bd0274f | /meteor/inst/testfiles/ET0_PenmanMonteith/AFL_ET0_PenmanMonteith/ET0_PenmanMonteith_valgrind_files/1615842016-test.R | 6b5da9b6d4a174c6b0080c0805ca9c6a0c6acce3 | [] | 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 | 619 | r | 1615842016-test.R | testlist <- list(G = numeric(0), Rn = numeric(0), atmp = numeric(0), ra = numeric(0), relh = numeric(0), rs = numeric(0), temp = c(-3.17097179177133e+148, -1.43300663669206e+306, 2.30235576924981e-92, -1.13144054336032e+193, -2.14555482385481e+110, -2.14555482385487e+110, -2.14555482385487e+110, -2.... |
eee8605acfa3fde8c65a632f7151dae13b04e79b | a8244362d0abccf33407e925d8d49251a03e4ed4 | /code/01-data-cleaning-scripts/02-biodepth-data.R | 843f712babfaca999ea498f08eb6b6471f48e9aa | [] | no_license | FabianRoger/Multifunc_Lund | 110b15a1d1bfb10703e059a3eb697b9abf5ee5a3 | d28ed79f9b05a2dac5622f5d8c9d1a99a29b4fbd | refs/heads/master | 2023-08-17T02:38:50.077334 | 2023-08-16T14:39:23 | 2023-08-16T14:39:23 | 205,349,586 | 1 | 6 | null | 2020-09-18T09:19:38 | 2019-08-30T09:25:31 | R | UTF-8 | R | false | false | 2,039 | r | 02-biodepth-data.R | #'
#' @title Download and clean the BIODEPTH data
#'
#' @description Load the BIODEPTH data taken from Byrnes et al. (2014, Methods
#' in Ecology and Evolution), clean it and output a cleaned version for
#' further analyses
#'
# load relevant libraries
library(dplyr)
library(multifunc)
# get the BIODEPTH data
data... |
6616aebc610c54a2212ba9353813b019bafe9212 | 809619e09165bb59d4b068eb8bad833d0a30c411 | /R/reportRelatedFunctions.R | 7cf287e45cb23ef0678297a22a1d50eda65cfedd | [] | no_license | cran/GWASinspector | 2910c12799e24c0c7e9f34df871f7d19c658c36a | 5fabba85bf8d9ce8eb30c51344be4cb4a59489fe | refs/heads/master | 2023-05-24T16:53:12.048188 | 2023-05-15T17:30:02 | 2023-05-15T17:30:02 | 236,609,635 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 31,675 | r | reportRelatedFunctions.R | create_report_files <- function() {
# print_and_log('\n','info')
print_and_log('============== Creating Report Files ==============',
'info')
if(!.QC$pandoc.exists)
print_and_log('pandoc module is required for converting report to Html format! check the manual on how to install.','w... |
b4e79811d94acb0496ac8534e62784428959f1f0 | 08b6d63a87add543e5aab98aab3386ece7aeef1c | /helpers.R | 036c5283d81ad47992da0673e431a54ba24eaa80 | [] | no_license | cyn2903flo/data_r | 5bc148a86fb70eae013396ae1fc4c185ef586101 | 8ca6f64a91401d64bf2d29d9c06f60148f88baea | refs/heads/master | 2022-12-28T17:07:03.395867 | 2020-10-14T21:19:11 | 2020-10-14T21:19:11 | 295,245,051 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,270 | r | helpers.R | # Function to form a one sentence summary from a year
# of annual data
summarize_park <- function(one_year){
comma <- scales::label_comma()
one_year %>%
glue::glue_data(
"En { year }, { park_name } se tuvieron { comma(recreation_visits) } visitas."
)
}
# Takes annual data and produces a pl... |
4ee319ce8caad1e2046d44a5c2ae83453f0a6661 | f9ee0159033cfecdf34c94b1cea99db0cc9f88b6 | /inference/collate-comparisons.R | c98f1aee692c87d418a140840f041f8df33dd0bb | [] | no_license | petrelharp/tortoisescape | 75cce4bea5c921f261506e6e382dadd15456f750 | 4e769efdaabf16e13c690510719bf26228880e58 | refs/heads/master | 2020-04-15T22:03:47.835144 | 2018-08-10T04:32:42 | 2018-08-10T04:32:42 | 23,332,197 | 1 | 1 | null | 2017-06-12T22:00:46 | 2014-08-25T23:33:02 | HTML | UTF-8 | R | false | false | 5,186 | r | collate-comparisons.R | #!/usr/bin/Rscript
usage <- "Collate results produced by comparison-results.R, stored in the .RData files passed in as arguments.
Usage:
Rscript collate-comparisons.R (outfile) ( file names )
"
argvec <- if (interactive()) { scan(what='char') } else { commandArgs(TRUE) }
if (length(argvec) < 2) { stop(usage) }
... |
b3a3abf3902002dc4cfc2574ce67d886aaeb5ac8 | 5419f18469d8308f34a37a1c74d7156130b45573 | /data_analysis/data_analysis.r | 6632cb4efbac1f39447577dca0ebb1933da738bf | [] | no_license | i-pan/i2b2-HST2014 | aa95e153321c1f737f8c4cd3cbf84706dcc4e4d7 | 6ba11a648d3a917886f08a9b77721cf129b29930 | refs/heads/master | 2021-01-23T07:30:05.188861 | 2015-01-23T21:16:28 | 2015-01-23T21:16:28 | 29,753,061 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 14,639 | r | data_analysis.r | ##### RUNTIME #####
ptm <- proc.time()
##### LOAD LIBRARIES #####
library(survival)
library(locfdr)
set.seed(10)
##### LOAD DATA #####
dem <- read.csv('dem.csv') # demographics file
dx <- read.csv('dx.csv') # diagnostics file
# phewas groupings, obtained from:
# http://knowledgemap.mc.vanderbilt.edu/research/cont... |
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