similar to: Homogenous groups building - Randomisation

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, I would like to build N "tkentry" compounds in the same window, with default text for each. As N is variable I need to construct them in an iterative way : library(tcltk) main<-tktoplevel() tktitle(main)<-"My Tool" filenames<-c("toto","tata","titi") N<-length(filenames) for (i in 1: N) {

Dear R-users, We expect to develop statistic procedures and environnement for the computational analysis of our experimental datas. To provide a proof of concept, we plan to implement a test for a given experiment. Its design split data into 10 groups (including a control one) with 2 mesures for each (ref at t0 and response at t1). We aim to compare each group response with control response

Hi, Is anyone has solved MR Xin Meng problem (see below) ? We have the same analysis configuration : 10 groups (including control one) with 2 mesures for each (ref at t0 and response at t1). We expect to compare each group response with control response (group 1) using a multiple comparison procedure (Dunnett test). In order to perform this test, we have to normalize our data (as you) to

Dear R-users, We expect to develop statistic procedures and environnement for the computational analysis of our experimental datas. To provide a proof of concept, we plan to implement a test for a given experiment. Its design split data into 10 groups (including a control one) with 2 mesures for each (ref at t0 and response at t1). We aim to compare each group response with control response

Dear R-helpers, We marked 6000 leaves from 5 SPECIES - 10 individuals/species - in two different TREATMENTs: a control and a dry-plot from which 50% of incoming precipitation was excluded. We followed those leaves for 42 months and noted the presence and absence at each visit. I then carried out a Cox Harzard model to see differences in leaf mortality between parcels and among species over time:

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

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 want to ue a randomisation test, to compare two sample means, for a small set of data, I've looked at towt.permutation, perm.test and permtest, as well as permTS(), which is the best one to use for such a simple purpose? I know perm.test package isn't used anymore and coins recommended, but reading the manual I couldnt find the function most like it, ore more likely I

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

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

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

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

On Wednesday 04 Apr 2012 13:27:07 Tim Northover wrote: > Putting that information in the InputArg/OutputArg and incorporating it the > CCAssignFn interface allows a more straightforward implementation in the > targets, in my view (for both our uses). It's also information that's > readily available when InputArg/OutputArgs are being constructed. In your > case: > >

Dear all, is there any possibility to generate a table of homogeneous subsets for multiple comparison tests as in SPSS with R? I am specially interested in Tukey's B test. I have tried to find the answer myself and found an excellent description here: http://www.ppsw.rug.nl/~sda/siv/Posthoc_print.pdf (-> Tab. 2) Together with the information here ...

Hello and thanks in advance I am running a glm in R the code is as follows with residual diagnostic code below model4<-glm(Biomass~(Treatment+Time+Site)^2, data=bobB, family=quasi(link="log", variance="mu")) par(mfrow=c(2,2)) plot(model2) to test the effect of grazing exclusion of feral horses for a Phd with following factors: Treatment - 3 levels which are grazed

Hi Tim > I'm not sure I follow this point. Is preserving the source language a bad > thing for some reason I'm missing? Certainly, if it affects optimisation it > would be. Let's consider one example: union { float foo[4]; int bar[3]; }; This is definitely not a HFA. However, such a union can be represented via several different things in LLVM IR: [4 x float], [4 x

Hi, I'm studying math, and i have to make an analysys using Randomised Block Design. I have two factors, i know how to do this in Statistica, but how to do this in R, i read some manuals but the only thing that i have found was 2 factor ANOVA. Please could someone help me, or give some usefull links ?? Krzytsztof Suwada

Hi all, I think that ABI of LLVM IR level is different from ABI on real architecture such as ARM or x86. ABI of LLVM IR level doesn't consider about register usage. It just describes parameters and padding information related to alignment of parameters. As Anton mentioned, LLVM have expressed ABI information on bitcode using front-end. If someone wants to maintain information from high level

Tim, > Opinions, anyone? (Hint hint). I think here stuff should be thought of from different points. While providing source type for argument might be beneficial, it might cause moving the code from frontend to backend. Consider e.g. passing struct by value including crazy padding inside. The ABI might specify that padding should be removed and struct is passed field-by-field. Also, note that