similar to: cross validation and parameter determination

Hello. Slope estimates in lme are shrinkage estimates which pull the OLS slope estimates towards the population estimates, the degree of which depends on the group sample size and the distance between the group-based estimate and the overall population estimate. Although these shrinkage estimates as said to be more precise with respect to the true values, they are also biased. So there is a

Hi All, Sorry if this is a repost (a quick browse didn't give me the answer). I wonder if there are packages that can do the feature selection and classification at the same time. For instance, I am using SVM to classify my samples, but it's easy to get overfitted if using all of the features. Thus, it is necessary to select "good" features to build an optimum hyperplane (?).

Dear friends - a couple of papers in PNAS (lastly:framework for making better predictions by directly estimating variables' predictivity, Lo et al PNAS 2016; 113:14277-14282) have focused interest on mapping complex traits to multiple loci spread all over the genome. I have been around on the relevant taskview(s) I hope but fail to see that the backward haplotype transmission association

Dear All, I've read Thomas Lumley's fortune "If the answer is parse() you should usually rethink the question.". But I am not sure it that also applies (and why) to other situations (Lumley's comment http://tolstoy.newcastle.edu.au/R/help/05/02/12204.html was in reply to accessing a list). Suppose I have similarly called functions, except for a postfix. E.g. f.1 <-

Dear All, I've got into the habit of installing R from the precompiled Debian binaries, including many of the packages from the r-cran-* Debian packages, and later building from source (e.g., to link against Goto's BLAS, or to build patched versions, etc). I install the newly built R to the very same place (/usr/lib/R). This allows me to build and update R when I wish, AND provides the

Dear List, We are planning a genotyping study to be analyzed using false discovery rates (FDRs) (See Storey and Tibshirani PNAS 2003; 100:9440-5). I am interested in learning if there is any consensus as to how many features (ie. how many P values) need to be studied before reasonably reliable FDRs can be derived. Does anyone know of a citation where this is discussed? Bill Dupont William D.

Hello! I'm calling R from Perl with Statistics-R perl module for a microarray analysis integrated web tool. I have some questions for a multi-users utilisation: - Can I change the directory where R is running in order to have a directory per user? Then no problem of erasing R data of an other user. - If it's not possible, can I limite the number of users at the same time? I see

Is there a colinearty function implemented in R? I have tried help.search("colinearity") and help.search("collinearity") and have searched for "colinearity" and "collinearity" on http://www.rpad.org/Rpad/Rpad-refcard.pdf but with no success. Many thanks in advance, Peter Lauren.

Hi, does anybody know how to use the dual processors in the machines of a cluster? I am using R with rpvm and snow packages. I usually start pvm daemon and add host machines first, and then run R to start my computing work. But I find that only one processor in each machine is used in this way and the other one always stays idle. Is there any simple way to tell pvm to use the two processors at

Hi everyone, I am trying to cross-compile a package I wrote using the Yan and Rossini tutorial "Building Microsoft Windows versions of R and R packages using Intel Linux". I have got reasonably far with this but when doing the linking using the line: i586-mingw32-g++ -shared -s -o mylibrary.dll mylibrary.def mylibrary.o mylibrary_res.o

Greetings! I have a few colleagues who like the idea of Sweave, but have failed to become enlightened monks of the One True Editor (http://www.dina.dk/~abraham/religion/) Are there any other Microsoft-centric editors or IDEs which have solid support for writing SWeave documents (dual R / LaTeX enhancements similar to ESS's support)? Has anyone tried the folding editors which support Noweb?

hi. i really need help using this program. computer language is a foreign language to me, and thus, i cannot make heads nor tails of the user manuals from the website. i need to locate step-by-step examples of simple problems such as "graph f(x)+g(x) and f(g(x)) for the domain 0<x<2" and "graph 2H(x), H(x)+1, H(x+1)" i do know how to define the functions, but

Dear all, not really a R question but: If I want to check for the classification accuracy of a LDA with previous PCA for dimensionality reduction by means of the LOOCV method: Is it ok to do the PCA on the WHOLE dataset ONCE and then run the LDA with the CV option set to TRUE (runs LOOCV) -- OR-- do I need - to compute for each 'test-bag' (the n-1 observations) a PCA

Dear list, I do apologize if these are basic questions. I am fitting some GAM models using the mgcv package and following the model selection criteria proposed by Wood and Augustin (2002, Ecol. Model. 157, p. 157-177). One criterion to decide if a term should be dropped from a model is if the estimated degrees of freedom (EDF) for the term are close to their lower limit. What would be the

Hi Everyone, I have a question about for loops. If you have something like: f <- function(x) { y <- rep(NA,10); for( i in 1:10 ) { if ( i > 3 ) { if ( is.na(y[i-3]) == FALSE ) { # some calculation F which depends on one or more of the previously generated values in the series y[i] = y[i-1]+x[i]; } else { y[i] <- x[i]; } } } y } e.g. >

Hi Everyone, I have a question about for loops. If you have something like: f <- function(x) { y <- rep(NA,10); for( i in 1:10 ) { if ( i > 3 ) { if ( is.na(y[i-3]) == FALSE ) { # some calculation F which depends on one or more of the previously generated values in the series y[i] = y[i-1]+x[i]; } else { y[i] <- x[i]; } } } y } e.g. >

Hello everyone, I've been fiddling around with the snow and Rmpi packages on my new Intel Mac, and have run into a few problems. When I make a cluster on my machine, both slaves start up just fine, and everything works as expected. When I try to make a cluster including another networked machine it hangs. I've followed the suggestions at

Hi, I am trying to understand the alternative methods that are available for selecting variables in a regression without simply imposing my own bias (having "good judgement"). The methods implimented in leaps and step and stepAIC seem to fall into the general class of stepwise procedures. But these are commonly condemmed for inducing overfitting. In Hastie, Tibshirani and Friedman

Hi I am using boosting for a classification and prediction problem. For some reason it is giving me an outcome that doesn't fall between 0 and 1 for the predictions. I have tried type="response" but it made no difference. Can anyone see what I am doing wrong? Screen output shown below: > boost.model <- gbm(as.factor(train$simNuance) ~ ., # formula +

Hi, I have optimized the shrinkage parameter (GCV)for ridge and got my r2 value is 70% . to check the sensitivity of the result, I did permutation test. I permuted the response vector and run for 1000 times and draw a distribution. But now, I get r2 values highest 98% and some of them more than 70 %. Is it expected from such type of test? *I was under impression that, r2 with real data set