similar to: Question about permutation test

Hello! So I am handling this problem with some arrays grp1-grp7, I want to write a loop to avoid tedious work, but I don't know how to transform string to boor? For example I used i=1 paste("grp",i, sep="") I only got "grp1" instead of grp1, which can't be manipulate using mean() or other function. I am not sure if I make myself clear... THANKS!!!!

I saw the manual of this function but not sure what to do. I have a array contain 7 numbers and want to choose 4 to do permutation test. But using this function with parameters as onet.permutation(scores,4), it returns 0. Instead, with no parameter, onet.permutation(), it returns something but every time it's different. Please tell me how am I supposed to do it. Thanks a lot -- View this

Hi! I am doing a two sample permutation test and trying to find confidence interval. perm.test() seems can do that but when the vector contains negative numbers it occurs an error. And for perm.test(x,y), elements in x can't be more than in y. I am wondering how I can fix these two problems? Thanks a lot. -- View this message in context:

Hi everyone, I am somewhat new to R and I am trying to write a permutation function such that it inputs a character vector and from an arbitrary length "n" which is the length of the combinations for the character vector. I know there are R packages for permutation but this is for an assignment. So far this is what I have: alphabet =

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 =

With a has_one/belongs_to relationship, what''s the best way to guarantee that the belongs_to object gets created and is accessible alongside the has_one object? I *think* the after_create callback is a good choice, but I discovered an oddity while trying it. F''rinstance, if every horse has a carriage: ============ ActiveRecord::Schema.define do create_table(:horses) {|t|

Apropos the question about permutation tests in multiple regression: We do have perm.test in package ExactRankTests, but it does one- and two-sample tests, as in t.test, wilcox.test, etc. There doesn't seem to be an exact version of the permutation test for correlations, i.e., the one that could be estimated using replicate(10000, cor(x,sample(y))) # or other values of 10000 or, of course,

Hi, I have a little problem that puzzles me about contradictory results returned by a bootstraped t-test (as in MASS 3rd ed p. 146) versus a permutation t-test (as in MASS 3rd ed, p 147). Data are measurements done on 100 cells in 9 slides of fish blood. With one method, cells are randomly sampled, and with the other method, the operator selects cells arbitrarily (in a way it is done usually

Dear R users, I am trying to perform a hypothesis test on a marked point pattern. I would like to calculate the mean of the absolute value of the difference of marks between nearest neigbours, randomize the marks among points, then calculate this mean again. Ideally, I would test whether random mean values smaller than the observed mean value occur less than 5% of the time. I suppose 1000

Dear R Programmers, I am trying to run a Poisson regression on all pairs of variables in a data set and obtain the permutation distribution. The number of pairs is around 100000. It seems my code will take weeks to run, unless I try something else. Could you give me any suggestions on how to improve the speed of the code below, or any general suggestions on how I may accomplish this task. Thanks

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 all Consider the classic data below from Darwin on the heights of 15 pairs of zea mays (corn) plants either cross-fertilized or self-fertilized, where the goal is to see if it makes a difference. > head(ZeaMays) pair pot cross self diff 1 1 1 23.500 17.375 6.125 2 2 1 12.000 20.375 -8.375 3 3 1 21.000 20.000 1.000 4 4 2 22.000 20.000 2.000 5 5 2 19.125

Hi, 1/ I wonder why a anova.lme on a single lme object does not print the sum of squares (as expected from the help: "a data frame with the sums of squares, numerator degrees of freedom, denominator degrees of freedom, F-values, and P-values"). Example: > fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1) > anova(fm2) numDF denDF F-value p-value

R users, Is it possible to do 'exact' permutation tests in R? If I run a perm.test or permutation.test.discrete on a data set that has, for example, 720 possible permutations, will that test permute ALL of those possible permutations, or will it just permute 720 random permutations (thus allowing some possibilities to repeat and some not to be permuted at all)? I'm a little confused

Dear R users, i am fairly new to R and am having trouble creating code to solve a problem. I've searched the list, combed Crawley's 'R book' and several others, but can't quite find what i want. I want to generate permutations of various 'blocks' of 14 numbers. Each number within a block is a character state for a particular biological taxon. In the example below, for

I am looking for an algorithm (written in R (preferably) or C, but even pseudo-code in a text book maybe fine) to determine the sign of a permutation. What is that? Well, a permutation is either even or odd, the sign is +1 or -1, respectively, see, e.g., http://en.wikipedia.org/wiki/Signature_of_a_permutation which also says >> In practice, in order to determine whether a given

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

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 users, This is a second summary of the permutation problem I previously posted. This summary restates the problem as well as the solution. First of all thanks to everyone including Erich, Robin, Gabor, Christian, Ingmar and others for your suggestions. With the help of an off-list discussion with Gabor I?m going to summarize. THE PROBLEM We have 12 elements in blocks of 3 : 1 2

Hi all, Suppose we have the following matrix m <- matrix(c(1,2,3,2,1,3,3,1,2), ncol = 3, byrow=T) where in each row each number occurs only once. I'd like to define a permutation, e.g. 1 -> 2, 2 -> 1, 3 -> 3 and apply it to the matrix. Thus, the following matrix should result: m.perm <- matrix(c(2,1,3,1,2,3,3,2,1), ncol = 3, byrow=T) i.e. each 1 should map to 2 and vice