similar to: Mantel's randomization test

Hello, I have output that I want to print out. I am having a few issues. 1] output u to power is really nothing more than a 2 x 11 set of values formed using cbind function and printed out as a data frame How can I get it to output over several lines such as seen here? 2] Critical Z etc. were added by hand. I need an example of how I can mix alphanumeric and numeric data on

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I've been attempting to understand the one-sample run test for randomness. I've found run.test{tseries} and run.test{lawstat}. Both use a large sample approximation for distribution of the total number of runs in a sample of n1 observations of one type and n2 observations of another type. I've been unable to find R code to generate the exact distribution and would like to see how

Hi, I've got a dataset with 7 variables for 8 different species. I'd like to test the null hypothesis of no difference among species for these variables. MANOVA seems like the appropriate test, but since I'm unsure of how well the data fit the assumptions of equal variance/covariance and multivariate normality, I want to use a permutation test. I've been through CRAN looking at

Hi, I'm interested in incorporating some interaction terms between my explanatory variables (distance matrices in this case) when I'm using the function MRM of the package ecodist. The function is doing a multiple regression on distance matrices. I can get the function to work perfectly on my explanatory matrices by adding a (+) sign as known. However, when I try to use the (*) sign or

I would like to perform partial mantel tests on only within group values, with "between group" values assigned to NA. This is possible in package ncf partial.mantel.test, however this sues a different permutation to that used in ecodist.ecodist will not accept data with NA values, returning a "matrix is not square error. is it possible to perform this test in ecodist? many thanks

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

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

Dear R-users, While making a prediction using the randomForest function (package randomForest) I'm getting the following error message: "Error in predict.randomForest(model, newdata = CV) : No forest component in the object" Here's my complete code. For reproducing this task, please find my 2 data sets attached ( http://www.nabble.com/file/p17855119/data.rar data.rar ).

OK, I'm mostly through everything up to and including Chapter 5 in http://www.redhat.com/docs/manuals/dir-server/8.1/install/Installation_Guide-Advanced_Configuration-Making-DS.html And looking through the ToC for the rest, I do not see that my questions will be answered by this doc. So please feel free to point me to other docs. This manual seems to assuming I already know what it is I

Could not find it in ?randomForest. Thank you for your help! -- Dimitri Liakhovitski Ninah.com Dimitri.Liakhovitski at ninah.com

Hi, I am trying to use a mantel test on two distance matrices. The code I have entered for each is: Gen_dists <- read.csv(file.choose(), stringsAsFactors = FALSE, na.strings = c(" "), fill = T,

Pierre Legendre has developed a beta version of a new redundancy analysis package called RdaTest that is available on his web page at the Universit® de Montréal. The test example that is included with the package is based on the example provided in his book (Numerical Ecology, Chapter 11 (Legendre & Legendre 1998)) I have downloaded the package and am attempting to run it so that I might

Hello, *Error in tx %*% comb : non-conformable arguments* Suggestions greatly appreciated. I am a beginner and this is my first time posting. I would like to get the summary for indicator species analysis, using package indicspecies with multipatt. I am getting errors, I believe, do to my data organization. After reorganizing and reorganizing, nothing has helped. > data<-

Hi! I am trying to analyse my data using amova (http://www.oga-lab.net/RGM2/func.php?rd_id=pegas:amova): My input to R is a DNA sequence file, format=fasta dna<- read.dna("XX.fasta", format="fasta") #left other options as default d<- dist.dna(dna, model="raw") g<- read.table("XXX.design") Load necessary libraries: library(pegas)

Dear R gurus I?m trying to use the GSCA package to a series of microarray data (prostate cancer normal vs tumor (29 vs 29 paired)) but I?m running into some problems. I have a matrix (named /data_final/) with 11k rows(genes) and 60 cols (58 samples (29N vs 29T), GO IDs, KEGG IDs). I also have a separate vector GS with the GO IDs mapped to genes (no duplicate genes but multiple IDs per gene like

Hi every body: I need some help with kendall.global. The example in the manual seems not working well, and cannot used with my data, always the same error. data(mite) > mite.hel <- decostand(mite, "hel") > > # Reproduce the results shown in Table 2 of Legendre (2005), a single group > mite.small <- mite.hel[c(4,9,14,22,31,34,45,53,61,69),c(13:15,23)] >

Dear all, Can anybody tell me how to export a 3d figure made with the plot3d function? I'm careless about whether it's still interactive or not in another format, as long I can get it out of R. Thanks! Alejandro Gonz?lez Departamento de Biodiversidad y Conservaci?n Real Jard?n Bot?nico Consejo Superior de Investigaciones Cient?ficas Claudio Moyano, 1 28014 Madrid, Spain Tel +0034

Hi *, is there a way to obtain some kind of p-value for a model fitted with RMA using the lmodel2 package? I know that p-values are discussed and criticized a lot and as you can image from my question I'm not very much of a statistican (only writing my bachelor thesis). As fare as I understood the confidence interval statistic correctly, a coefficient is regarded as statistically significant

Dear list, I would like to export a matrix to a TXT-File by using write.csv (not necessarily). Is there a way to add a header (with additional informations concerning the project) spanning multiple lines to this file before the actual data are listed up? Should look like this: date: filename: number of permutations: ------------ data (as a matrix) Any suggestions? Thnx in advance.