similar to: error using lapply with oneway_test (coin package)

Dear fellow R users, Keywords: Kruskal-Wallis, Post-Hoc, pair-wise comparisons, Nemenyi-Damico-Wolfe-Dunn test, coin package, oneway_test I am using the "oneway_test" function in the R package "coin" and I am obtaining results which I cannot believe are accurate. I do not wish to waste anyone's time and so if the following problem is rather trivial, I apologize, however I

Dear Researchers, Sorry for this email but I am not a statistician, and for this I have this problem to understand. Thanks in Advance for help and suggestions. Gianni I have 21 classes (00, 01, 02, 04, ....,020) with different length. I did a kruskal wall test in R with the following code kruskal.test(m.class.l, m.class.length.lf) Kruskal-Wallis rank sum test data: m.class.l and

Dear R-users, I am currently writing an R package that contains three C++ files in the src/ source directory When i issue a R CMD check pkge_name, all the *.cpp files in the src/ directory will be compiled through something like (seen in 00install.out file): * Installing *source* package 'pkge_name' ... ** libs g++ -I/usr/lib/R/include -I/usr/lib/R/include -I/usr/local/include -c

Hi, I'm trying to run a permutation test on paired samples. First I tried the package "exactRankTests": require("exactRankTests") x <- c(1.83,0.50,1.62,2.48,1.68,1.88,1.55,3.06,1.30) y <- c(0.878,0.647,0.598,2.05,1.06,1.29,1.06,3.14,1.29) wilcox.test(x,y,paired = TRUE,alternative = "greater") perm.test(y,x,paired = TRUE,exact = TRUE,alternative =

Using the package ?exactRankTests? one can execute a one-sample permutation test for a hypothesized location parameter of 0 like: perm.test(rnorm(30,0)) The package ?exactRankTests? seems now to be deprecated in favor of the ?coin? package which as I understand is a superset of ?exactRankTests? in terms of functionality. The ?coin? package allows one to run a two-sample permutation test using

Dear all, I've discovered the possibility to do the Nemenyi-Damico-Wolfe-Dunn test in the library(coin); oneway_test() With the given example I am unfortunately not able to reproduce the test. What does trafo and contrMat mean? I have a dataframe with 176 elements in 7 classes. It may be a problem, that my model isn't balanced? In Class1 I happen to have 4 elements, while there are 90 in

Full_Name: Drouilhet R?my Version: 1.8.1 OS: Linux Submission from: (NULL) (195.221.43.136) qchisq(1,10) works well but qchisq(1,10,ncp=0) does not work whereas ncp=0 is the default value of the function qchisq(1,10). (of course, 10 will be replaced by any integer value). Let us notice that this bug occurs only when applying probability one. (qchisq(seq(0,.9,.1),10,ncp=0) works very well).

Dear R users, When i call the wireframe function from within a tcltk widget, it does not work. Here is a sample program that shows the bug. When you try: is.it.a.bug() You can see that the "curve" instruction is run but not the "wireframe" one. Do you have an explanation about this point? Best regards, Pierre Lafaye de Micheaux -- Pierre Lafaye de Micheaux Bureau

I am trying to do a Nonparametric Tukey-type multiple comparison post-hoc test to determine which groups are significantly different. I have read the dialogue on this topic from the R-help, and am still not clear why no statistical packages include this test as an option? Is it not an appropriate test to conduct on non-normally distributed data? Is the only option to calculate it by hand

Hi R users! I have the following problem: how appropriate is my aov model under the violation of anova assumptions? Example: a<-c(1,1,1,1,1,1,1,1,1,1,2,2,2,3,3,3,3,3,3,3) b<-c(101,1010,200,300,400, 202, 121, 234, 55,555,66,76,88,34,239, 30, 40, 50,50,60) z<-data.frame(a, b) fligner.test(z$b, factor(z$a)) aov(z$b~factor(z$a))->ll TukeyHSD(ll) Now from the aov i found that my model

hi, as I'm using R at Dell (where I am working), I manage to install packages from web, but there is a web proxy, which is pretty boring. R asks me to enter an active directory login/password, that would normally auth me through the web proxy, but it doesn't work. I'm looking forward for your help. Sorry if I used bad english. Any ideas ? Laurent -- «Un peu d'internationalisme

Dear R users, I would like to know if there is a way in R to execute a post-hoc test (factor levels comparison, like Tukey for ANOVA) of a non-parametric analysis of variance with kruskal.test() function. I am comparing three different groups. The preliminary analysis using the kruskal-wallis-test show significance, but I still don''t know the relationship and the significance level

Given the following data, and hypothesized median M.0 I've found a method to implement the Wilcoxon signed-rank test. Data: (with one zero difference and tied ranks) x <- c(136, 103, 91, 122, 96, 145, 140, 138, 126, 120, 99, 125, 91,142, 119, 137) M.0 <- 119 > library(exactRankTests) Package ?exactRankTests? is no longer under development. Please consider using package ?coin?

Hi, R allows me to run a one sample Wilcoxon test like this: wilcox.test(c(1,3.5,2.1,4,1.5,5), mu=2, exact=TRUE) The function 'wilcoxsign_test' from the package 'coin' should (I suppose) be able to calculate exact p values even if there are ties in the ranks. However, I couldn't find information on how to run a one sample test using 'wilcoxsign_test' like in the

I am using "apply" to run exact permutation t-tests by columns using the coin package. For example: library(coin) dat <- matrix(rnorm(7*35),7,35) fun <- function(x) { pvalue( independence_test(x~f, data=data.frame(x, f=factor(c(rep("a",4),rep("b",3)))), distribution = "exact")) } p.vals <- apply(dat, 2, fun) Some small-scale

Hi, I am trying to make use of "approximate" option to obtain null distribution through Monte-Carlo resampling, as described in coin library documentation. Unfortunately, this does not play well with my data -- permutation process swallows astonishingly large amounts of RAM (4-5Gb) and runs far too long (30 min for B=10). Apparently, this is caused by the size of my dataset (see

Dear List, I'm interested in performing a permutation test on the interaction between a binary treatment indicator and a covariate (either continuous or categorical). I'm interested in the p-value of the interaction effect from a permutation test, and I'm using the coin package for that purpose. As I haven't seen any examples like this in the package documentation (or anywhere

Hi all, is it possible to perform a linear-by-linear association test (lbl_test, package coin) for a SINGLY ordered table ? And, if yes, how to manage the "scores" ? Thanks in advance Gilles - France [[alternative HTML version deleted]]

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Conditional Inference Procedures in a Permutation Test Framework The `coin' package implements a general framework for conditional inference procedures, commonly known as permutation tests, theoretically derived by Strasser & Weber (1999). The conditional expectation and covariance for a broad class of multivariate linear statistics as well as the corresponding multivariate limiting