similar to: permutation distribution for Friedman test

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

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

Hello everyone, I am looking at the joint spatial distribution of 2 kinds of organisms (estimated on a grid of points) and want to test for significant association or dissociation. My first question is: do you know a nice technique to do that, considering that I have a limited number of points (36) but that they are repeated (4 times)? I did GLMs to test for correlations between the

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

I am using the function permutations from the package *gregmisc*. However, I am also making use of the package *e1071*, which also contains a function called permutations. I want to use the function permutations from the * gregmisc* package, however, the other package is masking this function. This happens both when I load the *e1071* package before *gregmisc* and when I load *e1071* after I load

Hi, Is there any way to find the permutation function of the sorting and to apply the function (or its inverse) elsewhere? For example, the following permutation function from the sorting in the matrix form is c(1,2,3), c(2,1,3) > sort(c("bc","ac","dd")) [1] "ac" "bc" "dd" I try to find it in the permutations/permute

The gregmisc package contains a function 'perumutations' which generates all permutations of n choose r. It also contains 'combinations' which generates all combinations, and which appears to match your example: > library(gregmisc) Loading required package: MASS Attaching package `gregmisc': The following object(s) are masked from package:base :

> On May 22, 2018, at 10:57 PM, John <miaojpm at gmail.com> wrote: > > Thanks, David. > I got the answer from the web. > Is there any easy way to permute a set (e.g., a set of characters) by the permutation it returns? Thanks, > > > > x <- c(10,7,4,3,8,2) > > sort(x, index.return=TRUE) > $x > [1] 2 3 4 7 8 10 > > $ix > [1] 6 4 3 2

Hello All, Suppose that I have a sequence of letters (e.g., A..Z). I want to permute the sequence to generate random sequences, such that the local density of any letter with a window (say of length L) doesn't change much before and after permutation. One way that I can thing of is to require that the position of any letter in the original sequence and the position of the same letter in the

Thanks, David. I got the answer from the web. Is there any easy way to permute a set (e.g., a set of characters) by the permutation it returns? Thanks, > x <- c(10,7,4,3,8,2) > sort(x, index.return=TRUE) $x [1] 2 3 4 7 8 10 $ix [1] 6 4 3 2 5 1 2018-05-23 10:49 GMT+08:00 David Winsemius <dwinsemius at comcast.net>: > > > > On May 22, 2018, at 10:06 PM, John

> On May 22, 2018, at 10:06 PM, John <miaojpm at gmail.com> wrote: > > Hi, > > Is there any way to find the permutation function of the sorting and to > apply the function (or its inverse) elsewhere? > > For example, the following permutation function from the sorting in the > matrix form is > c(1,2,3), c(2,1,3) > >>

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

Hello, Like David said, what you are trying to do with sort() can be done with order() in a much easier way. First, your code x <- sort(c("bc","ac","dd"), index.return=TRUE) Now, with function order() i <- order(c("bc", "ac", "dd")) y <- c("D","E", "F")[i] y #[1] "E" "D"

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,

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

> sort(c("bc","ac","dd"), index.return=TRUE) $x [1] "ac" "bc" "dd" $ix [1] 2 1 3 We have the permutation, namely 1-->2, 2-->1, 3-->3. How can I apply the permutation function to a new set c("D","E", "F")? so that the result is c("E","D", "F"). 2018-05-23 11:06

Hi everybody, I'm trying to analyse a set of data with a non-normal response, 2 fixed effects and 1 nested random effect with strong heteroscedasticity in the model. I planned to use the function lmer : lmer(resp~var1*var2 + (1|rand)) and then use permutations based on the t-statistic given by lmer to get p-values. 1/ Is it a correct way to obtain p-values for my variables ? (see below)

Hallo Is there an elegant way to do the following: Dataset consists of 2 variables: var1: some measurements, and var2: a grouping variable with two values, 1 and 2. There are (say) 10 measurements from group 1 and 15 measurements from group 2. The idea is to study the permutation distribution of mean(group 1) * mean(group2). One way would be to permute 1s and 2s and select the corresponding

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

Hi, I have a complex-valued vector X in C^n. Given another complex-valued vector Y in C^n, I want to find a permutation of Y, say, Y*, that minimizes ||X - Y*||, the distance between X and Y*. Note that this problem can be trivially solved for "Real" vectors, since real numbers possess the ordering property. Complex numbers, however, do not possess this property. Hence the