similar to: Marginal Homogeneity tests for sparse matrixes ?

Hello everyone, Could you please help me find out if R supports matrixes inside matrixes? This is what I would like to do I have an area map of humidity per km. I would like at every cell to keep also information about the height of this area, the current temperature etc. Is something like that supported? I would like to thank you in advance for your help Best Regards Alex

Hola! I am working on a problem where data points are (square) matrices. Is there a way to make a "vector" of matrices, such that it can be stored in a data.frame? Can that be done with S3? or do I have to learn S4 objects & methods? Kjetil

Hello, I'm am in the process of trying to port a RATS functions to R and have the problem, that RATS allows for the creation of submatrixes that are linked to their basematrix. Basically it should work like this: a = matrix(1:(4*3),4,3) a # [,1] [,2] [,3] # [1,] 1 5 9 # [2,] 2 6 10 # [3,] 3 7 11 # [4,] 4 8 12 # This of course doesnt work :) b =

In a package I've been developing for manipulating genetic data I discovered a problem when indexing into character arrays using NA's: Create a character matrix and a numeric matrix > cmat <- matrix( letters[1:4], ncol=2, nrow=2) > nmat <- matrix( 1:4, ncol=2, nrow=2) Create an index vector containing an NA value > indvec <- c(1,2,NA) Indexing works fine for both

Hi, I have a function which does a certain task with two vectors, f1 <- function(a,b){body} I also have a list of matrixes (all with the same dim's), and for each column of each matrix in the list I want to use "f1", in such way that it gives the vector "a" in the first argument of "f1". The second argument of the function "b" also comes form a

Hi List. It may be a very simple question, but I couldn’t find an answer on the internet. Which function (maybe in a specific package) would I use to perform a Cochran C Test for Homogeneity of Variances? Stats package have the mantelhaen.test, but I’m “almost sure” that It’s not what I want, it’s probably the Cochran Q Test. So, any ideas? Thank you for the pacience.

Dear r-helpers, Prior to analysis of variance, I ran the Boxcox function (MASS library) to find the best power transformation of my data. However, reading the Boxcox help file, I cannot figure out if this function (through its associated log-likelihood function) corrects for * normality only * or if it also induces * homogeneity of variances *. I found in Biometry (Sokal and Rohlf, p. 419)

Hi, All! To calculate Levene's Test for Homogeneity of Variance I use R Commander, and this is the output: > levene.test(Dataset$age, Dataset$sex) Levene's Test for Homogeneity of Variance Df F value Pr(>F) group 1 0.8739 0.3567 33 I am not sure what means "Pr(>F)"? Can anyone explain/translate this? Regards, Iurie Malai Department of Psychology and

I partly answered my question since independence_test() function in coin package apparently do Cochran-Armitage trend test just like Eric Lecoutre's function tabletrend() - slightly modified here: > independence_test(pheno ~ geno, data = dat2, teststat = "quad", scores = list(geno = c(0, 1, 2))) Asymptotic General Independence Test data: pheno by groups 1 < 2

Dear Group Members, Forgive me if I am a little bit out of subject. I am looking for a good way to test the homogeneity of two variance-covariance matrices using R, prior to a Hotelling T test. Youll probably tell me that it is better to use a robust version of T, but I have no precise idea of the statistical behaviour of my variables, because they are parameters from the harmonics of

I am testing the homogeneity of variances via bartlett.test and fligner.test. Using the following example, how should I interpret the p-value in order to accept or reject the null hypothesis ? set.seed(5) x <- rnorm(20) bartlett.test(x, rep(1:5, each=4)) Bartlett test of homogeneity of variances data: x and rep(1:5, each = 4) Bartlett's K-squared = 1.7709, df = 4, p-value =

Hello! I've a problem with the combn function and a set of vector. I would like to make a simple combination where, instead of scalars, i would like to combine vector, in order to form matrixes. In other words, i have nineteen 6-items vectors (for example coef1-coef19), that i would like to combine in n!/k!(n-k)! 6x6 matrixes. I tried with a code like this mma <-

Dear all, I'm a beginner of R and I need to carry out some three-way mixed ANOVAs. Following examples at http://personality-project.org/r/r.anova.html, I managed to get the ANOVA part, but I don't know how can I check data normality and homogeneity of variance in R (since they're the required assumptions of ANOVA analysis). Are there any special command/packages? Could anyone give me

Dear all I have two 10*10 matrixes and I would like to compare theirs contents. By the word content I mean to check visually (not with any mathematical formulation) how similar are the contents. I also know edit that prints my matrix in the scree but still one edit blocks the prompt to launch a second edit() screen. What is the best way to compare these two matrices? I would like to thank you

Today's R 1.9.0 beta: > m1 [,1] [,2] [,3] [,4] [1,] NA NA NA NA [2,] NA NA NA NA [3,] NA NA NA NA [4,] NA NA NA NA > class(m1[1,1]) [1] "list" > cbind(m1,m1) Error in cbind(...) : cannot create a matrix from these types > rbind(m1,m1) Error in rbind(...) : cannot create a matrix from these types > version _

Has the Levene test of homogeneity of variance been implemented in any library in R? Thanks, Maurice Haynes National Institute of Child Health and Human Development Child and Family Research Section 6705 Rockledge Drive Bethesda, MD 20892 Voice: 301-496-8180 Fax: 301-496-2766 E-Mail: mh192j at nih.gov

Hello best helpers, I am a new user and I have been struggling for hours. So finally I decide to ask you: If I have a matrix P, and P.2 = P%*%P, and P.3=P.2%*%P is there a function to calculate the power of a matrix?? if not how can i do: for (i in 1:10) {P.i=P^i} after this I need to sum them up and my problem is to combine P and i to P.i can anyone help me please??? Thanks and have a nice

Dear all, I would like to multiply two matrixes with the different dimension column by column. Let make an example: If I have two matrixes "X" and "Y"as follow: X<- matrix(1:12, nrow=4, ncol=3, dimnames=list(c("A","B","C","D"), c("stage1","stage2","stage3"))) Y<- matrix(1:28, nrow=4, ncol=7,

Hello all, I'm running very simple regression but face a problem of non-homogeneity of variance, but with a decreasing variance with increasing mean...I do not know how to deal with that. this relationship doesn't seem to be strong, but it's my first time to see something like that, and would like to know what to do if one day it becomes stronger. I tested just for fun some

Dear all, I have been trying to find a function to calculate the Breslow-Day test for homogeneity of the odds ratio in R. I know the test can be preformed in SAS but i was wondering if anyone could help me to perform this in r. In addition i have the fullrefman file to search for functions in the basic R packages, does anyone have any suggestions of an efficient way of searching for