similar to: Randomisation tests

Dear listers, I was used to package pgirmess under Windows with everything OK, but, for the first time, I had a trial this afternoon on Ubuntu 7.10 gutsy (I have a double boot computer and work more and more under unix) and R 2.7.0. Everything went OK except this: sudo R CMD check pgirmess ..... * checking examples ... ERROR Running examples in 'pgirmess-Ex.R' failed. The error most

Hello everybody, I have a question. I would like to get a correlation between constitutive and induced plant defence which I messured on 30 plant species. So I have table with Species, Induced defence (ID), and constitutive defence (CD). Since Induced and constitutive defence are not independant (so called spurious correlation) I should do a randomisation test. I have a syntax of my

Hi to all, I am looking for a randomisation procedure for a single matrix, including a possibility to set the number of randomisations and the to set the number of row and columns . Knut

Hi, I have two groups of data of different size: group A: x1, x2, ...., x_n; group B: y1, y2, ...., y_m; (m is not equal to n) The two groups are independent but observations within each group are not independent, i.e., x1, x2, ..., x_n are not independent; but x's are independent from y's I wonder if randomization test is still applicable to this case. Does R have any function

Dear useRs I am looking for a way to randomise the values within a matrix: the conditions are that the sums of the rows and the sums of the columns should remain the same as in the original matrix. Any help would be appreciated Cheers Yann

Hi, I've got a dataset with 7 variables for 8 different species. I'd like to test the null hypothesis of no difference among species for these variables. MANOVA seems like the appropriate test, but since I'm unsure of how well the data fit the assumptions of equal variance/covariance and multivariate normality, I want to use a permutation test. I've been through CRAN looking at

Consider the following simple example using R-2.9.0 and 'perm' 2.9.1: > require('perm') > p<- c(15,21,26,32,39,45,52,60,70,82) > g<- c('y','n','y','y', rep('n',6)) #Patients ranked 1,3,4 receive treatment > permTS(p ~ g, alternative = 'two.sided', method='exact.ce') #find p-value by complete enumeration

Dear R-people, I hope asking this is not too cheeky, but I do have a R Problem. I hope that some of you like to play around with R and can help me. Its like this. I have several plant species (A,B,C) and 10 replicates per species. 5 plants per species are damaged, 5 not. I let a caterpillar feed on each plant and measured the growth of the caterpillars on control plants (CR) and on damaged

Hello, In an attempt to randomise the basic blocks in a function, is it possible that I can randomise the entry block as well? And maybe insert some instructions in the pass to call entry block while running the program ? Is it feasible? What does entry block consist of ? Thanks Tanu --------------------------------- Do you Yahoo!? Yahoo! Search presents - Jib Jab's 'Second

Tanu Sharma wrote: > Hello, > > In an attempt to randomise the basic blocks in a function, is it > possible that I can randomise the entry block as well? And maybe insert > some instructions in the pass to call entry block while running the > program ? > > Is it feasible? > > What does entry block consist of ? The entry block, by definition, is the first basic

Hi! I am experiencing troubles concerning the inheritance of the setgid bit if a new mailbox is created with dovecot-lda. If it is created with dovecot/imap, everything works fine. dovecot-lda is called from postfix like this: ---------- mailbox_command = /usr/local/sbin/postfix-lda.sh ---------- logger -p mail.info -t postfix-lda "H: $HOME, S: $SENDER, R: $RECIPIENT, U: $(umask), id:

Dear all, The other day I was reading this post [1] that slightly surprised me: "To reject the null of no correlation, an hypothsis test based on the normal distribution. If normality is not the base assumption your working from then p-values, significance tests and conf. intervals dont mean much (the value of the coefficient is not reliable) " (BOB SAMOHYL). To me this implied that in

I am now writing an R code to do the systematic permutation test and the random permutation test. And I encountered a couple of problems which I cannot figure them out. At first, whenever I type "permtest" in my R2.6.1, it always shows:"there is no such a function", I tried again and again and eventually I found I have to use "library (BHH2)" before I use

Hello I'm very much a beginner on meta-analysis, so apologies if this is a trivial posting. I've been sent a set data from separate experimental studies, Treatment and Control, but no measure of the variance of effect sizes, numbers of replicates etc. Instead, for each study, all I have is the mean value for the treatment and control (but not the SD). As far as I can tell, this forces

Dear R-users, We expect to create N homogenic groups of n features from an experimentation including N*n mesures. The aim of this is to prevent from group effects. How to do that with R functionalities. Does anyone know any methodes enabling this ? Best regards. Alexandre MENICACCI Bioinformatics - FOURNIER PHARMA 50, rue de Dijon - 21121 Daix - FRANCE a.menicacci at fr.fournierpharma.com t??l

Dear R-users, We expect to form N homogeneous groups of n features from an experimentation including N*n data. The aim is to prevent group effects. How to do that with R functionalitites ? Does anyone know any way enabling this ? Example : 100 patients are observed. 3 biochemical parameters are mesured for each one (Red and white globules ans glycemia). Patient RG RW

Hi all, As part of some recent work to harden the Kernel Address Space Layout Randomisation (KASLR) implementation in arm64 Linux, I've proposed a patch for the kernel which omits the ESR context from the signal frame if the faulting virtual address is outside the range of addresses which can be mapped by userspace. http://lists.infradead.org/pipermail/linux-arm-kernel/2018-March/563837.html

Dear All, I get the following error when using either SASxport or Hmisc to read an .xpt file: > w <- read.xport("D:/consult/Trophos/dnp/base/TRO_ds_20081006.xpt") Erreur dans factor(x, f$value, f$label) : invalid labels; length 15 should be 1 or 14 > z<- sasxport.get("D:/consult/Trophos/dnp/base/TRO_ds_20081006.xpt") Erreur dans factor(x, f$value, f$label) :

On 03/06/2018 08:58 PM, Will Deacon wrote: > Hi all, > > As part of some recent work to harden the Kernel Address Space Layout > Randomisation (KASLR) implementation in arm64 Linux, I've proposed a > patch for the kernel which omits the ESR context from the signal frame > if the faulting virtual address is outside the range of addresses which > can be mapped by userspace.

This uses time, ASLR and pid for randomisation. (Closes: #516774) Signed-off-by: Thorsten Glaser <tg at mirbsd.org> --- usr/include/stdlib.h | 2 + usr/klibc/Kbuild | 2 +- usr/klibc/mkstemp.c | 93 ++++++++++++++++++++++++++++++++++++++++++++++++++ 3 files changed, 96 insertions(+), 1 deletions(-) create mode 100644 usr/klibc/mkstemp.c diff --git a/usr/include/stdlib.h