similar to: Problem with approximate null distribution (package: coin)

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

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]]

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

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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

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

Hi, I am running the following example which can be found on page 12 of the pdf file of COIN package wt<-wilcox_test(pd~age,data=water_transfer,distribution="exact", conf.int=TRUE) "wt" actually contains the estimate of difference in location and the confidence interval of it. I am just wondering how can I extract these values? From the examples, I understand that the

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 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,

All, I've devised a way to toss a coin three times and record the number of heads, then use the table command to summarize the number of time 0, 1, 2, or 3 heads were obtained. n <- 100 x <- sample(c("H","T"),3*n,replace=TRUE) dim(x) <- c(3,n) num_heads <- apply(x,2,function(x) sum(x=="H")) table(num_heads)/n What I'd like to do next is run this

Good Evening R-Help Community: I have attached a file that contains the output from sessionInfo() and a summary of my Win XP system. I am?running R 2.12.0 and using Tinn-R 2.3.6.2 as my interface. When I attempt to call either the doBy or coin packages R generates an error that I do not understand and have so far not been able to resolve by searching R resources. I exchanged a couple of

Is it possible to implement the Jonckheere-Terpstra test for ordered alternatives using the coin package: Conditional Inference Procedures in a Permutation Test Framework? I found jonckheere.test{clinfun}, but it uses a normal approximation when ties are present in the data. To make this concrete, I've include a small dataset. Thanks. --Dale Hollander and Wolfe, 1999 Table 6.6, pg 205

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,

Hi, Dear R community, These is a paper of "Wheat Grain Yield Response to N Application Evaluated through Canopy Reflectance". This paper of "Materials and Methods" said "A single regression equation relating A and B was derived for each location using PROC NLIN (SAS Inst. 1990). Slopes and intercepts for the independent regressions were compared with an *approximate

Hello! I am using relatively simple linear model. By applying fastbw() on ols() results from rms package I would like to get subtable "Approximate Estimates after Deleting Factors". However, it seems this is not possible. Am I right? I can only get coefficients for variables kept in the model (for example: x$coefficients), but not S.E., Wald's Z and P? Is there any easy way to

Hi All, Say I have the values of function f(x1,x2,x3,x4) for each values of x1,x2,x3,x4 but not complete. But the functional form is not known. Techniques like regression, etc. are not able to give me satisfactory results and msy be more complex than we thought. I wanted to use Taylor's approximation to continuous function, to approximate a functional form using the given data. But failed