similar to: autologistic model? - what package?

Dear all, I have one Model (M3) fitted using the lme package, and I have checked the correlation structure of within-group errors using plot(ACF (M3,maxLag=10),alpha=0.05) But now I am not sure how to interpret this plot for the empirical autocorrelation function. The problem is that I am used to see/interpret diagrams in which all the autocorrelation Lags, except lag-1, are inside the

Hello! Could anyone please tell me how should I include R in a text section for References? Regards, Sara Mouro [[alternative HTML version deleted]]

Dear All, I have to enter many lines of data in the same object. I usually use copy-paste to transfer data from an Word file to R. But, for large lines of data, R gets "confused" and gives an error message, i.e. it breaks one line somewhere, and lines get no meaning at all. Some times I solve that problem adding "enters" and making each line shorter, before I do

Dear all I can not understand how to install the package lpsolve_1.1.9.zip I have read the FAQ and the help pages carefully, but it still not clear for me. I have tried the following (and obtained the respective error messages): >install.packages("c:/ProgramFiles/R/rw2011/library/lpSolve_1.1.9",destdir=" c:/ProgramFiles/R/rw2011/library/lpSolve") Mensagem de aviso:

Hi, I am new to autologistic regression and R. I do have questions when starting a project in which I believe autologistic regression is needed. I have a point layer whose attribute table stores the values of the dependent variable and all the independent variables. I hope to to fit an autologistic model to analyze which factors or combinations of factors have effects on the presence/absence of

Dear all, How can I explian and solve the error message: "margins too large" which appears when I do something like: KK <- alltypes(SpatData, "K") plot.fasp(KK) Hope someone can please help me on this. Regards, Sara Mouro [[alternative HTML version deleted]]

Dear R users, I have this 2 models that fit to my data: M3varI <- update (M3, weights=varIdent(form= ~ 1|SITE)) M3AR1<-update(M3,correlation=corAR1()) The first one, updates my M3 so that I can account for the variance structure of random erros. The second one, updates my M3 so that I can account for the correlation structure of random errors. How can I put them toghether in one

Hi, I have spatially autocorrelated data (with a binary response variable and continuous predictor variables). I believe I need to do an autologistic model, does anyone know a method for doing this in R? Many thanks C Bell

Dear all, I have read the on-line explanations I have found about Building R from sources, and istalling Packages from sources... Also, I have installed gcc4.0 and the gfrotran-4.2.1.dmg. However, I still do not know how to use them to compile one Source (in particular packfor_0.0-7.tar.gz) so that I can use it in R (for MAC OS X). Could someone please explain it to me in an easiest way

Dear all, Does any one knows why should I get the following error message, when trying to do a simple data.frame?? DataF<-data.frame(Subject,BiomR,Spp,Capas,Litter,Herbs,LitterD,MaxCanH,DDifS p,DSSp,Slope, CanDens,NearestSp) Erro em data.frame(Subject, BiomR, Spp, Capas, Litter, Herbs, LitterD, : arguments imply differing number of rows: 202, 0 The data I am using

Hello! I am writing you because I could not plot the confidence envelopes for functions Jest, Jcross, Jdot, Jmulti, and L, using the Spatstat package. I have already understood how to do that for Kest or Jest, that is: JEnv <- plot(envelope(PPPData, Jest)) Where PPPData is my ppp object. However, for Jcross I must specify the two marks I want to analyse. That is, usually I would get the

Hello everyone, I have some binary, spatially autocorrelated data I would like to run autologistic regression on. I hope to incorporate both ordinary covariates (environmental predictors) and a spatial autocovariate in the model, ideally with a second-order neighbourhood structure. Since my computing skills are limited, I am wondering if anyone has composed an algorithm for this purpose, and

> > Dear all, > > I have been usig R for some time, but now I have a MAC instead of a > PC, am I am having problems in reading files... > > > I have tried: > Data<-read.table("Users/SaraMM/PhD/Analises-LitterBags/Dados- > Litter.txt",head=T) > > but it said: > Error in file(file, "r") : unable to open connection > In addition:

Dear all, I am using the nlme package to find the best model using non-linear mixed effects model. After the all the other things needed, I did > M1<- nlme(NShrubs~A*exp(-B*CED),data=DataSg,fixed=list (A~SITE,B~1), random=B~1,start=list(fixed=c (1.66,1.66,1.66,1.66,1.66,1.66,1.66,1.66,0.0038)),control=lmc) and it was ok. However, the data showed to need random parameters at both

Dear all, Sorry for such basic question, but. when R "says": library(Rcitrus) Loading required package: geoR Loading required package: sp ------------------------------------------------------------- Analysis of geostatistical data For an Introduction to geoR go to http://www.est.ufpr.br/geoR geoR version 1.6-8 (built on 2006/06/29) is now loaded

Hi all, I am trying to run an autologistic model using the function errorsarlm from spdep package. **I built an XY matrix extracting the two colums from matriz** coords1<-matriz[matriz$casos1==1, c(4,5)] coords1<-as.matrix(coords1) **I identify neighbours of region points** nb20<-dnearneigh(coords1,0,20,longlat=TRUE) ** I build a neighbours list with spatial weights**

Hi all, I am whitening my data: # code begins N <- 300 M <- 2 x <- matrix(data=rnorm(N*M, 0, 3)-10, ncol=M, nrow=N) y <- matrix(c(1,-2,-2,1), ncol=M, nrow=M) z <- data.frame(x %*% y) colnames(z) <- c('x','y') par(mfrow=c(1,3)) plot(z, pch=5, col="blue") whiten <- function(x) { (x-mean(x))/sd(x) } zz <- transform(z, x=whiten(x), y=whiten(y))

Dear all, I am a beginner with lpSolve package (and not an expert in the others). I can not understand why I am doing wrong, and I would be very grateful if anyone could please help me on this. I am trying to optimize ("min") the sum of columns/variables, constrained to >=1. Each column/variables has its weight - given by values at f.obj. The matrix for numeric constraint

Dear All, Can I solve a "Set Covering Problem" (in a mathgraph) using R? Which package should I use for that? Thank you in advance. Sara Maltez Mouro [[alternative HTML version deleted]]

Dear all, I am using the spatstat package, but my field data was a mirror image of the data plotted by plot.ppp(X). Therefore I changed it using -x and -y coordinates. However, I guess (I saw "debug") that I get some error messages because of that. So, could anyone please tell me if I really can not use negative values for x and y coordinates in a ppp.object (and relates analysis)?