similar to: logistic regression model validation through bootstrapping

Hi All, I had a look in archives but no joy. I just want to know before i deploy - if there is any problem with having multiple rsync sessions from many source locations all to same destination server ( all copying to different file systems obviously ) ?? Its jusat that i see on the destination machine a process rsync -server being called whenever a client connects. Thanks ! Laurence

I'm using /parApply/() function in "snow" package for parallel computing (boostrapping repeating calculation), as the follows: MyBoostrapping <- function( i ){ ..... } cl <- makeCluster( ncluster, type = "SOCK") i.circle <- as.matrix( 1:128, , 1) parApply( cl, i.circle, 1, FUN = MyBoostrapping) It works. However, I want to set more than one arguments to

Hello, I'm new to boostrapping and I'd need some help to understand the error message that pops up when I run my script. I have a data.frame with 73 lines and 21 column. I am running a stepwise regression to find the best model using the R function "step". I apply bootstrapping to obtain model coefficients. This is my script: # "datare80" is the name of the

Hello all. I have two small questions in one post, for the sake of brevity. 1. I have some objects that I want to delete. I have the line: rm (c (channelheader, paste ("channel", 1:3, sep=""))) I have tried a few variations, including list=, but cannot figure it out. In SAS, I can use a ':' as a wildcard. Is there any equivalent in R? 2. Is there any possible was to

We have a project on which we need to compare various methods for computing factor scores. Are there any R routines available that do parametric bootstrap or compute factor scores?

If anyone can help it would be very much apreciated... System RedHat 9 R installed as # ./configure --enable-R-shlib # make # make install and R seems to work fine ... Then I do # R INSTALL --clean --configure-args='--with-in-perl' RSPerl_0.5-7.tar.gz # export R_HOME=/usr/local/lib/R # cd /usr/local/lib/R/library/RSPerl/examples/ # perl -I

Just for the interest of discussion, I find it completely weird and interesting that GCC needs to build itself 3 times to fully bootstrap. Has there been any interest in looking at a single compile build? I don't exactly know the limitations, but my naive thinking is that C++14 compiler source parsed by C++14 capable compiler and codegen'd to C99 (or older) source should make it compilable

(Just returning from the "wilds" of Canada, so not able to comment on the specifics, but ...) There is a basic point about generic functions that may be related to the "private" class question and my earlier remarks that Martin alluded to. R (and S4 before it) allows packages to define methods for a generic function in another package. Say, for plot() in graphics. The

Dear R users, we are trying to do some parallel computing using library(snow). In particular we have a cluster with 3 nodes >cl <- makeCluster(3, type = "MPI") 3 slaves are spawned successfully. 0 failed. and we want to compute the function op_mat (see below) first with the master and then with the cluster using system.time for checking the computational performance.

I took my anaconda-ks.cfg file, cp to ks.cfg and copied to a floppy The isos have been copied to an ftp server. So I had the following lines in my ks.cfg intall url ftp://10.1.1.1// (yes the ftp server's directory is the Centos directory) This is along with all the appropriate network command to get the ethernet setup. I issue the linux ks=floppy (also tried linux

I realize questions about packages should go to the package maintainer, but perhaps I have an old email address (suzuki3 at is.titech.ac.jp) Also I have both a general, and a specific, question. 1) General question: i've used pvclust before to assess significance of clusters and got reasonable results. However, on a new data set (see below) the results seem odd. I wonder if pvclust is a

Hi All, I would like to do double boostrapping to estimate 95% CI coverage. So, I can only need to estimate 95% confidence interval from each bootstrapped sample. Since we don't have a closed form of 95% CI, in order to get 95% CI for each sample, we need to use bootstrapping. For outer bootstrapping, I used boot function in library(boot). How can I add double bootstrap inside the function.

Hi, Let me start my saying that I am new to R hence my grasp of the appropriate used of R coding is undoubtedly way behind many on this forum. I am trying to use boostrapping to derive errors around my parameter estimate for the fixed effects in the following model. It is simply estimating the number of times an animal might cross a road based on the road's distance from a stream. I have

Hi, I want to permutate the following matrix and replace permutated columns. Is it possible to control the number of columns permutated. Let's say I only want to permute two columns. Can i do that with the sample method or should i any bootstrapping method ?? I'm not sure this is the best statisticaly way of doing it...?? So the idea behind is to ramdonly generate 1000 permutated

I should add one more item that may be related here -- calling 'methods:::.requirePackage' returns a different result based on whether the package namespace is already loaded or not. If the package namespace is not loaded, the package is loaded and attached, and the package environment is returned: > methods:::.requirePackage("digest") Loading required package:

Hi Renato, On Tue, Oct 8, 2013 at 3:57 PM, Renato Golin <renato.golin at linaro.org>wrote: > On 7 October 2013 18:33, İsmail Dönmez <ismail at donmez.ws> wrote: > >> This is with Linux on BeagleBone Black (Cortex-A8), regressed recently: >> > > Hi Ismail, > > Are you running this regularly? Do you know which commit regressed? Or at > least a window?

Hi, The problem is modern c++. I can have a reasonable system boostrape-ed with (tinycc/alternative C compiler), but only in the gcc world since a modern c++ compiler is only bootsrape-able from near any C compiler there. clang and llvm are unable to do it. That why I would need to get 2 gccs: "any C compiler" -> gcc 4.7.4 -> gcc recent_version -> llvm. On Fri, Oct 14, 2016 at

On Wed, Oct 12, 2016 at 07:15:39PM +0100, Renato Golin wrote: > On 12 October 2016 at 18:37, <sylvain.bertrand at gmail.com> wrote: > > Suggestion is not clear answer. How such a decision taken? Is there a board of > > people which have to vote to valid the choice of minimal gcc (and clang) version > > effective? > > We don't have such process, unfortunately.

On Wed, Oct 12, 2016 at 04:15:44PM +0100, Renato Golin wrote: > On 12 October 2016 at 14:34, Teresa Johnson via llvm-dev < > llvm-dev at lists.llvm.org> wrote: > > > So I'd first like to understand whether we still want to keep gcc 4.7 as a > > supported version, or move to 4.8 as was suggested. What is the process for > > making that change? > > >

On Mon, Oct 17, 2016 at 11:28 AM, Renato Golin via llvm-dev < llvm-dev at lists.llvm.org> wrote: > On 17 October 2016 at 19:09, Flamedoge via llvm-dev > <llvm-dev at lists.llvm.org> wrote: > > Just for the interest of discussion, I find it completely weird and > > interesting that GCC needs to build itself 3 times to fully bootstrap. > Has > > there been any