similar to: increasing speed for permutations of glm

Dear R Users, I have the following glm, which I am running several times in a loop (I am not including the full code): reduced_model <- NULL; full_model <- NULL; reduced_model <- try(glm.fit(X4,n,family=poisson(link="log"))) full_model <- try(glm.fit(X5,n,family=poisson(link="log"))); On some occasions, an error is produced, which is why I have attempted to work

Dear R Users, I implemented a try() statement that looks like: <- function(index) { reduced_model <- try(glm.fit(X4,n,family=poisson(link="log"))) full_model <- try(glm.fit(X5,n,family=poisson(link="log"))) if (inherits(reduced_model,"try-error") || inherits(full_model,"try-error")) return(NA) else { p <-

Hi R-users I would like to extract the random effects ("1|SITE", "1+SPECIES|SITE" and "BA|SITE") from this model formula: Full_model <- formula (VAR ~ (1|SITE) + (1+SPECIES|SITE) + (BA|SITE) + HEIGHT + COND + NN_DIST) I tried: terms(Full_model) labels(terms(Full_model)) but I could not distinguish between random and fixed effects. thanks

I'm trying to do a Hosmer-Lemeshow 'goodness of fit' test on my logistic regression model. I found some code here: http://sas-and-r.blogspot.com/2010/09/example-87-hosmer-and-lemeshow-goodness.html The R code is above is a little complicated for me but I'm having trouble with my answer: Hosmer-Lemeshow: p=0.6163585 le Cessie and Houwelingen test (Design library): p=0.2843620

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'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

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 ).

Dear ecology fellows, I tried to implement Morisita-Horn distance (instead of Bray that is in the current version) in the code for the Simper analysis in vegan. I would be very grateful if someone can check if the code is right. function (comm, group, ...) { if (any(rowSums(comm, na.rm = TRUE) == 0)) warning("you have empty rows: results may be meaningless")

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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,

Dear all, Dose anyone know whether there is a good R packege or program for Mantel's randomization test? Thanks in advance. ------------------------ Takashi Mizuno zoono at sci.osaka-cu.ac.jp Plant Ecology Lab. Osaka City University ------------------------ -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

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)] >

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 *, 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

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<-

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