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As we train a neural network, we have access to the error-rate (both on training, and test patterns). What are standard techniques to use this information to stop the learning as quickly as possible when over-fitting starts?
|
I am reading a paper "A note on the Delta Method" by Gary Oehlert, JASA, 1992.
I am trying to estimate the variance of a function of a random variable, but first I want to understand the limitations of using the Delta Method Taylor series.
Oehlert states:$^1$
when the function we are approximating is polynomially bou... |
I've attended a course on Machine Learning and another one in Network Analysis, and I wonder if this two topics already intersect, in particular I'm interested in the following model:
we have a mobile network (that is, the nodes perform a random walk in some area, then sending a message within some assigned range, let... |
I have been playing around with post processing the results of the random forest for regression machine learning algorithm in order to try and do better than the default mean of all trees prediction. Chapter 16 of Elements of statistical learning talks about how and why this can be done using regularised regression (in... |
I have performed a 2x2 experiment to measure the effects of two genetic factors on the occurrence and size of a rare birth defect. When an individual has the defect, we can measure its size (size is a continuous value greater than zero, with no upper bound.)
Here is some size data similar to what we're seeing. When an ... |
Given a dataset X with N observations in 11 dimensions, where each variable is restricted to be >= 0, how is it possible to fit an 11-dimensional log-normal distribution to this dataset?
I only found sources for fitting an univariate lognormal to data, but I didn't find anything for the multivariate case.
I would be ha... |
I have posted a "similar" question in another thread. But I think that question is not specific/concrete enough to get the answer I expected.
I know that, in survival analysis, the concordance index (c-index) can be used to measure how well a ranking list is w.r.t survival times of subjects (F. E. Harrell, 1996, sectio... |
I'm performing the cox regression analysis, where I have the model with 1 time-independent (treatment (yes/no)) and 1 time-dependent predictor (blood pressure level).
Outcome is death (yes/no). Time until death is measured in days and the count starts after the date of treatment prescription (time=0 days) in patients.... |
I am told, in Gaussian Processes, adding covariance function noise to others, say SEiso or Materns, cause a better result, since it prevents from over fitting. I appreciate if someone could put more light on it !
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We have over 10 years of data on a number of hospitals that we regularly transport patients to. This past February, a new hospital (1830) opened that has substantially altered our transport patterns, especially taking away from the previous primary destination (1247).
Destination Dec Jan Feb Mar Apr
... |
I have a question about how to interpret a regression analysis I did following a factor analysis.
I did principal axis factoring (direct oblimin)
I got a 3 factor solution. The three factors were (1) feelings (2) kinship and (3) interactions. (I'm looking at father-child relationships)
Regarding factor loadings, (1) fe... |
I want to see if a datapoint x should (or not) be assigned to a nearest component y using the following condition:
if ($d > T$) then {do not assign x to y}. With $d = distance(x,y)$ and $T = \bar{d}+\sigma$ where $\bar{d}$ is the mean distance of y to datapoints that were already assigned to it in the past, and $\sigma... |
Dear Stack Exchange heroes,
For my thesis I am writing a paper on the financial crisis. In my model, I use two regressions, which look like this:
$$CONF = α + β_1 DEF_t + β_2 DIV_t + β_3 INF_t + β_4 IP_t + β_5 CONS_t + β_6 TBILL_t + β_7 URATE_t + β_8 NBER_t + β_9 DEF_{t-1} + β_{10} DIV_{t-1} + β_{11} INF_{t-1} + β_{12}... |
Let's take football (soccer) for example. There are 3 possible outcomes, home win, draw, away win. I took a random game from bet365
Turkey vs Ukraine
hwin, draw, awin
2.20 3.40 3.20
So for investment of 100\$ on given result, you either loose 100\$ or win: 220\$, 340\$ or 320\$. Their probability assessment doesn't ... |
I have estimated (MC simulated) some probability values y, that each depends on a value of x between 0 and 1.
Say, for instance, that the vector x contains
$x_{1} = 0.1,\ \ x_2 = 0.2,\ \ x_3 = 0.3,\ \ x_4=0.4,\ \ x_5 = 0.5,\ \ x_6 = 0.6,\ \ x_7 = 0.7$
and the vector of estimated mean values y contains
$y_{1}(x_1) = 0.... |
Robby McKilliam says in a comment to this post:
It should be pointed out that, from the frequentists point of view, there is no reason that you can't incorporate the prior knowledge into the model. In this sense, the frequentist view is simpler, you only have a model and some data. There is no need to separate the pri... |
I am trying to conduct a simulation study on a variation of the kernel density estimator. In that experiment, there is a parameter in one of my formulas that involves the value of the unknown pdf at a given point x. Therefore I need to find a consistent estimator to estimate the value of f(x), but I have no clues on wh... |
I'm an almost graduated applied math student. I do some sporadic work in marketing. I have done a few market segmentation projects. I am soon going to do one which is important to me. I usually segment customer types: in a questionnaire people are asked about how they "feel" or what they "like" or consider "important" ... |
I have been working on an inverse regression addon for SPSS and using this paper heavily:
I. Lavagnini, F. Magno, A statistical overview on univariate calibration, inverse regression, and detection limits: Application to gas chromatography/mass spectrometry technique., Mass spectrometry reviews 26, 1-18 (2007).
They do... |
My question may be very basic but I hope that you can help me.
I have got two groups (A and B). I am measuring two continuous biological measures (X and Y) which are significantly positively correlated. Theoretically it is clear that X can influence Y but not vice versa.
Y has been measured two times (Y1 and Y2) and sh... |
When using the forward stepwise approach to select variables, is the end model guaranteed to have the highest possible $R^2$? Said another way, does the stepwise approach guarantee a global optimum or only a local optimum?
As an example, if I have 10 variables to select from and want to build a 5-variable model, will t... |
I have some confusion regarding confidence interval.
I was going through this link http://www.stat.yale.edu/Courses/1997-98/101/confint.htm
It has something like this:
Suppose a student measuring the boiling temperature of a certain
liquid observes the readings (in degrees Celsius) 102.5, 101.7, 103.1,
100.9, 100.... |
I am trying to run a Dunnett's test on some toxicity data (comparing responses to a negative control), but need to compare more than 20 treatments to the control. I've written an R function to run the Dunnett's test by interpolating q' from the tables presented in Zar (1999), however the number of groups is limited to ... |
I want to actually get the confidence interval of gaussian distribution. I want to know how I can use the covariance matrix and check if the obtained mui vector for the multivariate gaussian distribution actually satisfied the confidence interval. I have a mui vector and the actual values to be obtained. How can I use ... |
I am trying to calculate interrater reliability in SPSS for both pre and post test of the same measure that is administered as part of a prison intake program. The measure has 20 items and then a total score. I am just running on total score agreement.
I ran crosstabs and calculated kappa for the pretest and correlat... |
Which may be good techniques to face this abstract problem?
You have a data stream of a continuous signal, as one from a physical sensor. That signal has real (discretized) values, no attribute; addictional features (e.g., power, auto-correlation, entropy) might be extracted. You can assign one label from a finite set ... |
I have proportion data where I am interested in the proportion of successes, but also in the number of successes. Is there some statistic I can calculate to summarize this info into one number?
Sample data:
X N P
2 4 .5
40 200 .2
3 10 .3
50 100 .5
Here the first and last data have the same proportion, ... |
A well-known result is that the only density that is both spherical and independent error is normal: more precisely
Let $e_i$ be errors,
If the joint probability density satisfies
$$f_n(e_1,e_2, ..., e_n) = f_1(e_1)f_1(e_2)...f_1(e_n)$$
(independence) and if it is spherical:
$$f_n(e_1,e_2, ..., e_n) = g_n(\Sigma_{i=... |
I know that widget X has a population of N_x. However, widget Y has an unknown population that I'd like to estimate.
Both widgets appear with a differential frequency over time as I sample them.
Time ... X counts .... Y counts
1 .......... 120 ............... 2
2 .......... 212 ............... 3
3 .......... 32... |
I asked a group of subjects to make a series of 12 binary choices regarding preferences.
Let's say for arguments sake, these were between ugly (ug), attractive (att), and neutral (neut) faces. Hence, we have 4 ug vs att, 4 ug vs neut and 4 att vs neut choices. For each subject I summed the number of times each face wa... |
Assuming I have a data set with $d$ dimensions (e.g. $d=20$) so that each dimension is i.i.d. $X_i \sim U[0;1]$ (alternatively, each dimension $X_i \sim \mathcal N[0;1]$) and independent of each other.
Now I draw a random object from this dataset and take the $k=3\cdot d$ nearest neighbors and compute PCA on this set. ... |
Context: I'm reading up on sampling in MCMC for Machine Learning. On page 5, it mentions rejection sampling:
repeat
sample xi ~ q(x) and u ~ U(0,1)
if uMq(xi) < p(xi):
accept xi
until enough samples
(where $M$ is chosen such that $p(x) \le Mq(x)$ for all $x$)
Question: In the analysis, the paper says that it m... |
The question is simply what is stated in the title: When does the law of large numbers fail? What I mean is, in what cases will the frequency of an event not tend to the theoretical probability?
|
I have a couple of measurements for an environmental variable on different locations (7 measurement stations) as time series with averages for every year.
For the single locations I have calculated the deviations of single years from the long term average.
The annual deviations are not normally distributed as there ar... |
We have created a questionnaire. In this questionnaire there are different dimensions with different answering scales.
Because of our rightly skewed data we log transformed our data. But here is the thing:
Because of the different answering scales (some are Likert 5, some Likert 7, and even a dichotomous scale) they ... |
Two letters are drawn randomly from the word SENSATION with replacement.
What is the probability that the letters will be identical?
Answer attempt:
there are 9 possible letters to be drawn
the letter S and N occur twice, making the probability of each S: 2/9, N:2/9
Now I'm guessing that the probability that the letter... |
Possible Duplicate:
Method to estimate the prediction interval for GLM and Negative Binomial distribution
I am trying to compute prediction intervals for GLM using either Poisson or Negative Binomial distributions.
First I developped a Monte-Carlo approach for Gaussian distribution and derived it for the other dist... |
Possible Duplicate:
Evaluate definite interval of normal distribution
Title was changed and question edited bellow.
How is possible that a probability density function defined as following can return some values that are higher than 1 ?! Is there any error in my definition of this pdf ?
float gauss_pdf = exp( -pow(x... |
I am using the limma package in R to do some analysis on a count data matrix. I use the voom function and that normally creates a plot with the mean variance trend line in it. Now I created also a mean variance trend plot, but it doesn't look normal.
Has anyone seen something like this before?
|
I am a bit confused when it comes to 68-95-99.7 rule of confidence interval of normal distribution. Normally I could see confidence interval of 95% for a sample statistic (s) with margin of error lets say e. So the confidence interval is s +- e. So 95% means that if we do the sampling 100 times and calculate the sampl... |
I have created a multi-channel object here:
https://github.com/aronlindberg/VOSS-Sequencing-Toolkit/blob/master/creating_multichannel_object.R
However, when I try to use various functions to describe the multi-channel sequences, I get errors saying that what I'm trying to process is not a sequence object.
I created my ... |
I am sampling from a parameter with unknown distribution. I would like to calculate a 95% CI for the standard deviation of the sample.
@cardinal provides a nice general solution for calculating a CI in his [answer] to my previous question, Calculating required sample size, precision of variance estimate?. And @erik-p... |
I have an empirically gathered dataset which relates two variables. Over a small range the relationship appears linear, however over a larger range there is clearly some second order polynomial relationship as can be seen in the image:
I'm trying to get a measure of linearity for different ranges considered. E.g. at 2... |
In his answer to my previous question, @Erik P. gives the expression
$$
\mathrm{Var}[s^2]=\sigma^4 \left(\frac{2}{n-1} + \frac{\kappa}{n}\right) \>,
$$
where $\kappa$ is the excess kurtosis of the distribution. A reference to the Wikipedia entry on the distribution of the sample variance is given, but the wikipedia pag... |
Consider two samples ${(x_i)}_{i=1}^m$ and ${(y_i)}_{i=1}^n$. Assume that the $x_i$ are independent replicates from a distribution with expectation $\mu_X$ and similarly the $y_i$ are independent replicates from a distribution with expectation $\mu_Y$, and also assume that the two samples are independent. Is it possibl... |
Given computed values for a box plot (min, lq, median, uq, max) and original raw data size is it possible to merge that with raw data.
given:
box1 = [min:1,lq:2,median:5,uq:8,max:10]
size1 = 50 #size of dataset that gave me the box1 calculated values
data2 = [1,1,6,...]
How can I combine both into a new box plot. Is t... |
Is there a multiple change point analysis for both the mean and the variance simultaneously, implemented in R without a distribution assumption?
I know the changepoint packet
http://cran.r-project.org/web/packages/changepoint/index.html
but as far as I see, it only allows change point analysis (mean & variance simulta... |
I am considering the following problem.
Calculate the exact probability that an algorithm classifies seven
wines out of ten correctly when the true error is 0.23.
Should I solve this with Bayes' rule?
|
When the large number law fails, the frequency of an event does not converge to the probability, so what is the meaning of probability in these cases?
PS: Please adds references to the answers (if it possible).
|
I have a series of electromyographic (EMG) reflex recordings, of which I would like to find out the principal components. My thoughts are that there are multiple processes that added together result in the EMG recording.
Here is a series of reflexes of a single recording
and here a single reflex
As you can see all r... |
I have some doubts about the covariance structure in a multilevel model fitted in R (using the nlme package). I'm not an expert (just starting to learn statistics...), so I apologize if some of my questions seem evident. I've checked the previous posts and haven't found an answer.
I have data from an experiment in whi... |
I've used rjags to run MCMC on a model, specified in the JAGS language. Is there a good way to extract that model and perform predictions with it (using the posterior distributions of my parameters)? I can re-specify the model in R and plug in the modes of my parameter posteriors; I'm just wondering if there's a less r... |
I am trying to create a variogram for a data set with 10,000 points. However, if I try to actually calculate the distance of each point with the other then I will have 10,000*9999/2 pairs. Out of these pairs of distances I can round off the distance values to lets say 2 decimal places. Then I can find the distances hav... |
I am working on a text categorization task, and I possess 21,000 documents for training, and (for the time being), 7000 documents for testing. I construct the doc-term matrix for both training corpus and testing corpus, with two different weighting factors, i.e. TF (term frequency) or TF-IDF (term frequency–inverse doc... |
I am using LibSVM library for classification. For my problem I am using polynomial kernel and I need to select best parameters (d = degree of polynomial kernel, and C = soft margin constant). The LibSVM guide suggests for grid search for this job. In this library there exists a parameter selection tool (grid.py), but i... |
I have a simple probability calculation I was working on that I came up with an answer for, but a question a colleague asked me led me to come up with a second approach - and a different answer. I put it aside at the time (a couple of years ago), but now it's niggling at me.
I think my original answer is correct becau... |
The instructor of the machine learning course I've been taking whipped this algorithm at my head without explaining how to apply it to a training set.
m = number of training sets (3)
j = subscript 0 or 1
x(i) = x from the ith training set
y(i) = y from the ith training set
alpha = ?
h theta = ?
If I had a training se... |
In my calculus class , we encountered the function $e^{-x^2}$, or the "bell curve", and I was told that it has frequent applications in statistics.
Out of curiosity, I want to ask: Is the function $e^{-x^2}$ truly important in statistics? If so, what is it about $e^{-x^2}$ that makes it useful, and what are some of it... |
I finished my B.S in Statistics in the early 80's. Recently, for a variety of reasons, I've got interested in Generalized Linear Models. Would you guys please point me some good books on the theory and applications of GLIM's? Any references with lots of worked examples, proofs of the main results, and many exercises wo... |
I have one dataset with currency exchange ratios for several years. The exchange ratios are for two Asiatic currencies and the Canadian dollar, all against American dollars. My (perhaps naïve) thinking is that I can observe which economies are more strongly tied by looking to the association strength between the ratios... |
Background:
I have two groups of children - one group with normal hearing and one with permanent hearing losses - call them NH and PHL.
Each child has had a hearing test, consisting of 6 different sounds (.25, .5, 1, 2, 4, and 8KHz) assessed under three different test conditions (classic, remote, and hybrid)
Each child... |
I used a Monte-Carlo approach to estimate the prediction interval for a new observation from a GLM using a Negative Binomial distribution. I used this method for linear models and got reliable estimations of the prediction interval but I am not enough confident with statistics to know if this method could also be appli... |
I am studying a complex system. My goal is to understand the impact of a spreading accident (which saturates the filter (sand and plant) and creates puddles). Puddles decrease the efficiency of the system (depollution of effluent, and moisture content). The impact on the efficiency will decrease with time (more or les... |
Maybe the dumbiest question ever posted on CV:
I want to analyze the relationship between proportion data and some covariates in a generalized linear (mixed, but I don't think it matters) model.
The natural distribution to use would be binomial but most of the proportions are close to 0 and their distribution looks lik... |
What is a good way to visualize high dimensional (say n=10) binary data? I remember reading something about that a few years ago.
Say for instance, you want to plot / cluster pizzas based on their topping, e.g. ham, chicken, mushrooms etc.
|
Is it possible to use common principal components for assessing covariance matrix similarity in R?
This approach was championed by Flurry, 1988 but this paper is what I have in mind.
References
Flury B (1988) Common principal components and related multivariate models. Wiley, New York
|
edit: tl;dr: I can coerce a lot of optimization problems to take the form of a non-linear least squares problem, but does it make sense to do so?
Suppose we have some empirical data $P=\{(x_i', y_i')\}_{i\in I}$. A non-linear least squares (NLLSQ) problem is one where we want to minimize a function of the form
$$S(\bet... |
Let's have some linear model, for example just simple ANOVA:
# data generation
set.seed(1.234)
Ng <- c(41, 37, 42)
data <- rnorm(sum(Ng), mean = rep(c(-1, 0, 1), Ng), sd = 1)
fact <- as.factor(rep(LETTERS[1:3], Ng))
m1 = lm(data ~ 0 + fact)
summary(m1)
Result is as fol... |
I am analysing data on 300,000 pupils in 175 schools with a logistic linear mixed effects model (random intercepts). Each pupil occurs exactly once and the data spans 6 years.
How do I partition variance between the school and pupil levels, in a similar way to the VPC/ICC for continuous outcomes ? I have seen this art... |
I have a clustering algorithm, where if I use an euclidian distance as similarity, it works well on any dataset. If I replace it by a cosine similarity (see my code bellow), it will give a degenerate results (will not work at all). Did I do an error in coding this cosine similarity or it is the cosine similarity that s... |
For example, I have three variables: A, B, C.
I analysis the partial correlation between A and B while controlling C (expressed as A~B[C]), and the partial correlation between A and C while controlling B (expressed as A~C[B]).
The result shows that the correlation coefficient of A~B[C] is 0.67, p-value < 0.001, however... |
I am doing research on the field of functional response of mites.
I would like to do a regression to estimate the parameters (attack rate and handling time) of the Rogers type II function.
I have a dataset of measurements.
How can I can best determine outliers?
For my regression I use the following script in R (a non l... |
Suppose you have a response variable, number of transactions a customer makes in the 24 hour period following acquisition, which follows a negative binomial distribution. Let's call the response trans.
Now it's easy to model the number of transactions the customer makes in this immediate 24 hour period, or trans, usin... |
I'm not sure if machine learning is the best way to do this, but I'm interested in seeing if this problem is feasible. Normally you use machine learning for classification. ie.given the size of a tumor and the color(darkness) of the tumor, determine whether its lethal or benign. However, say you want to figure out how ... |
As far as I know, one can calculate the relative standard error from the standard deviation of a data sample. I am looking for the Median Absolute Deviation equivalent for standard error.
Does one exist? Also which methods exist to calculate the relative standard error, that do not require the standard deviation?
|
I am using PCA on foreign exchange return series to find a market "beta". I am using 10 years of daily data with a 2-year half life weighting in the PCA using the package FactoMineR's PCA function. I extract the first principal component return series (so the product of the first eigenvector and the returns matrix) and... |
I have a certain population U. The members x of U each either satisfy or don't satisfy a property p. That is, p(x) is either true or false for each x in U.
I want to get an estimate of the fraction of members of U that satisfy p. I do this by repeatedly sampling from U (with replacement) for some fixed time such as ... |
I'm doing some object recognition, and when I compare two images, I get some unbounded "distance" between the two images, representing how similar they are. This is somewhat useful, but it seems like it would be more useful if I could move from this "distance" space into a probability space, where instead of " The dis... |
I am rather ignorant about nonparametric bootstrap. Assume the same context as in this question: ${(x_i)}_{i=1}^m$ and ${(y_i)}_{i=1}^n$ are independent data samples, the $x_i$ are independent replicates from a distribution with expectation $\mu_X$ and similarly the $y_i$ are independent replicates from a distribution... |
My research generates raw data from titrations that needs a substantial number of calculations before I get the numbers in a form that I can analyze. Most of these calculations are relatively simple unit conversions etc... Typically I create a spreadsheet in Excel to perform all of these calculations and then only im... |
I'm analyzing a double-blind, placebo controlled RCT using an ANCOVA in R, where the predicted "treatment effect" shows up before the treatment has occurred!
The goal of the study is to determine if treating a disease reduces a particular behavior. Folks with both the disease and the behavior were randomized 50-50 into... |
I've seen PCA improperly applied in genetic research quite often. I wanted to clarify : when is it appropriate to use PCA as a visualization tool in your analysis?
Some examples:
1) Rarely is the % variance reported for the components. With human data it's been my experience that the first three components (which are o... |
For a linear regression with multiple groups (natural groups defined a priori) is it acceptable to run two different models on the same data set to answer the following two questions?
Does each group have a non-zero slope and non-zero intercept and what are the parameters for each within group regression?
Is there, re... |
I am performing a regression on a large dataset that is fairly noisy. The line I am running in R is:
lmfit <- lm(predictVariable ~ dataSet[,1:10])
so I have 10 endogenous variables. The results are somewhat strange:
significant t-statistics for all the coefficients
$R^2 = 0.25$
But when I run a regression again on t... |
Many authors of papers I read affirm SVMs is superior technique to face their regression/classification problem, aware that they couldn't get similar results through NNs. Often the comparison states that
SVMs, instead of NNs,
Have a strong founding theory
Reach the global optimum due to quadratic programming
Have no ... |
I will be collecting data from three three different groups. I will be interviewing women (probabilistic sample) and then asking them to provide a name to build the other two groups (convenience sample). I would like to know what is the best approach to analyze all this data?
My study is about: Breastfeeding support in... |
In the setting of multivariate multiple regression (vector regressor and regressand), the four major tests for the general hypothesis (Wilk's Lambda, Pillai-Bartlett, Hotelling-Lawley, and Roy's Largest Root) all depend on the eigenvalues of the matrix $H E^{-1}$, where $H$ and $E$ are the 'explained' and 'total' varia... |
I am reading Modern Regression Techniques Using R (Wright and London, 2011).
At the end of the chapter on "Robust regression", in the summary of "Statistical concepts", there it says,
"to Tommy Franks: to ridicule the Geneva Convention*"
"* According to a quotation from the Lancet paper"
I can't figure what it tries ... |
In reading Blake Master's notes on Peter Thiel's lecture on start ups, I came across this metaphor of the technology frontier:
Picture the world as being covered by ponds, lakes, and oceans. You’re
in a boat, in a body of water. But it’s extremely foggy, so you don’t
know how far it is to the other side. You don’... |
Suppose $X\beta =Y$.
We don't know $Y$ exactly, only its correlation with each predictor, $X^\mathrm{t}Y$.
The ordinary least-squares (OLS) solution is $\beta=(X^\mathrm{t} X)^{-1} X^\mathrm{t}Y$ and there isn't a problem.
But suppose $X^\mathrm{t}X$ is near singular (multicollinearity), and you need to estimate the op... |
I have quite a general question about Variance-gamma distribution. I am interested in how to estimate it's parameters given a set of training points?
I tried to find the answer in the internet, but surprisingly managed to find only a couple of relative links:
VarianceGamma R package (and it's manual)
The paper which i... |
In a binomial experiment, if we observe $x=0$ positive individual among $n$ individuals, then the proportion of positive individuals is significantly lower than $3/n$ with a type 1 error less than and very close to $5\%$. This fact, sometimes called the "rule of three", is a consequence of the inequalities $$\exp\left(... |
I am constructing a Vector autoregression model and I have used AIC to find how many lags I should use. Does 7 lags seem unreasonable? I am trying to find the impact the property market has had on the economy and my variables are GDP, inflation, employment rates, housing prices, number of housing complete, long-term in... |
What approaches exist to observe the time lag between two variables?
I need to analyze the relationship between blood pressure and some other factor, such as exercise. The data set I am drawing from has around 1800 individuals, with an average of 100 entries a piece. It is generally known that there is a strong relatio... |
Consider these two grayscale images:
The first image shows a meandering river pattern.
The second image shows random noise.
I am looking for a statistical measure that I can use to determine if it is likely that an image shows a river pattern.
The river image has two areas: river = high value and everywhere else = lo... |
I´m trying to learn generalized mixed models in SAS and I have now bumbed into a situation that I cannot figure out by myself. So I was thinking that maybe some of you could help me forward.
I´m running a model where I have normally distributed measurements of traits like tarsus etc in birds from different populations.... |
I am trying to optimize the hyperparameters for a Gaussian process. As a starter I choose the squared exponential function for covariance where iI have to optimize 3 parameters $\sigma_f$, $\sigma_n$ and the length parameter $l$.
$$k_y(x_p,x_q) = \sigma^2_f \exp\left(-\frac{1}{2l^2}(x_p-x_q)^2\right) + \sigma^2_n\delta... |
I'm analyzing chemical profiles of amphetamine samples, and each sample has 26 numerical variables describing the relative quantity of some chemical constituent. Only a few of the 26 variables have pretty Gaussian distributions, the rest are amorphous (e.g. one very large "0" bin and a small Gaussian-like hill to the r... |
I'm attempting to develop a standardized method to check whether one set of locations are representative of a larger set. In this particular case, I'm attempting to look specifically at their geographical representativeness.
One method is to look at a two sample t-test for latitude and longitude * independently*, but ... |
I'm very new at statistics, so excuse me if my questions are to simple or obvious.
I have a dataset with response times for two conditions. These response times were converted into a binary score of either 0 (absence of the effect) or 1 (presence of the effect).
The experiment is designed in 7 blocks. For each block p... |
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