similar to: Singly ordered contingency tables with lbl_test (coin)

Hi everybody, I am a new R user. Is there any package devoted to "text mining" analysis in R ? Thanks Gilles lepape.gilles at neuf.fr

Hi, when performing a spearman_test stratified by a given factor in package "coin", how is it possible to obtain the value of Rho, the Spearman correlation coefficient ? Thanks in advance Gilles (F) [[alternative HTML version deleted]]

I all, is there a way with R to perform an exact permutation test to replace the wilcoxon test to compare paired series and/or to perform pairwise multiple comparisons for related series after a Friedman test ? Thanks Gilles

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

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

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Hi list, 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 (kruskal.test() function object). I was looking for something like the Dunn Test. I’ve searched the internet but nothing seemed to define a way to it. Do You have any suggestion? Other equivalent test maybe! Thanks in

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

Hi all, I am trying to analyze the following data. The first three columns are categorical variables (colors of three traits for a peripatus species) and the last column the count of individuals in each three-way classification. I wish to test if the three traits vary independently or if they are correlated across individuals, i.e. - this is a basic three way contingency table question.

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

Dear R helpers, I am trying to understand how to use the independence_test function in the coin package. I think I suffer from a misunderstanding about what the package does. Either that or I do not understand how to use it properly. Specifically, I cannot understand if I can test independence of arbitrary statistics. Take the following example: set.seed(10) d <- data.frame(y = c(rnorm(10,

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

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 R-list members, This is in fact a question about statistics, not directly about the R software. The coin package, for conditional inference through permutation methods, has as it main function the function independence_test. One of its parameters is teststat, about which the package documentation says: teststat: "a character, the type of test statistic to be applied: either a

I tried Tal's suggestion of deleting the doBy and coin packages and then reinstalling them from a different mirror. The first install was from the Harvard mirror and the second was from the Case Western Univ. mirror. The new packages generate the same errors when I call them using the library() command. Also, I tried to load these packages using R and its script editor thinking that the

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

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?

I am trying a simple toin coss simulation, of say 200 coin tosses. The idea is to have a data frame like so: Experiment# Number_Of_Heads 1 104 2 96 3 101 So I do: d <-data.frame(exp_num=c(1,2,3)); /* Just 3 experiments to begin with */ d$head_ct <-sum(sample(0:1,200,repl=TRUE)); d; exp_num head_ct 1

Dear expeRts, I would like to use a oneway_test (from package coin) to test whether two groups differ on various variables. The variables are encoded within a data frame. Unfortunately, I obtained an error, that I don't understand. Could you please help me ? Example: library(coin) y <- as.data.frame(matrix(rnorm(200), ncol=2)) group <- as.factor(unif(100)) lapply(y,

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