similar to: multiple autocorrelation coefficients in spdep?

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**

Dear list, (also sent to Roger Bivand, but perhaps somebody of you can help me also) I am trying to use package spdep for fitting an SAR model with errorsarlm. However, I am not sure how to make a valid nb object out of my neighborhood. As far as I have seen, there is no documentation for nb.object. I have done the following: class(pschmid$nb) <- "nb" # pschmid is a prab object as

Hello, I have been using the package "spdep" to run spatial regressions on a data set with about 2500 observations. It has performed well up until now, but the following code resulted in an error: > load("Panel.90s.ok.R") > attach(Panel.90s.ok) > neighs<-dnearneigh(cbind(x,y),0,50000) > help(nbdists) > dists<-nbdists(neighs,cbind(x,y)) >

Hello, I am trying to extract an estimator for the bread of the sandwich function. I used bread(fitted model) however it seems that I have missed something as an error message "no applicable method for "bread" appears. My fitted model is a Spatial simultaneous autoregressive error model.(errorsarlm in spdep package) Can anyone please tell me what I might be doing wrong? Your

Dear R community, I have a nonlinear model describing average daily soil temperature. What test should I use to compare differences in soil temperature of the two studied vegetation types depending upon month? Building linear contrasts for the developed nonlinear model does not help since this model does not include variable “Months” (only “Days”). 1) Just a Student’s test is not probably

Dear R community, I used a linear mixed model (named lm11) to model daily soil temperature depending upon vegetation cover and air temperature. I have almost 17,000 observations for six years. I can not account for autocorrelation in my model, since I receive the error message after applying the function: update(lm11, corr=corAR1()) Error: cannot allocate vector of size 220979 Kb Do

Dear R community, Below you may find the details of my model (lm11). I receive the error message "Error: cannot allocate vector of size 220979 Kb" after applying the autocorrelation function update(lm11, corr=corAR1()). lm11<-lme(Soil.temp ~ Veg*M+Veg*year, data=a, random = list(Site=pdDiag(~Veg), Plot=pdDiag(~Veg))

Dear R community, I used a linear mixed model (named lm11) to model daily soil temperature depending upon vegetation cover and air temperature. I have almost 17,000 observations for six years. I can not account for autocorrelation in my model, since I receive the error message after applying the function: update(lm11, corr=corAR1()) Error: cannot allocate vector of size 220979 Kb Do

Dear R community, Using nlme library I have developed a nonlinear mixed model. Incorporating an autoregressive model gives me an error that I can't allocate vector of size X. The problem is that my computer does not have enough physical memory most probably due to a large number of observations (17,000). I was wondering what alternative options I might use: 1) To use ARIMA and

Hello, When I was running CentOS 5.2 (and other Liuux distribution) on an Asus W2J laptop, I never get sound. I upgraded to CentOS 5.3. Now the sound card is recognized and plays the test sounds. I checked channels with alsamixer, mix, kamix .... I still have no sound using aplay alsa command or whatever else audio display. Trying to check my configuration I discovered that the snd-hda-codec.ko

Dear all, I have a question regarding the spdep package: Assume that each person within my dataset is characterized by a continuous variable y. In order to test for spatial autocorrelation in y I calculated a Moran's I statistic. The problem is that y is also likely to be influenced by a series of other variables x that are unique to each person in my dataset. To test to which extent the

Hi R helpers, Is there a function (package?) in R available which tests "spatial autocorrelation" between points (e.g. vector layer of weather stations)? (e.g. Moran's I...) Via the archives we found out that there is a package 'spdep' which uses grid data for testing spatial autocorrelation. Thanks a lot, Jan

Howdy All, I am looking for some good tutorials (books, websites, whatever) for calculating/testing for Spatial Autocorrelation using R. Specifically, I am wanting to test for autocorrelation of a number of variables measured at a set of discrete locations. Up to this point I have been exploring the "spdep" package and I can get "moran.test" to work, but I am concerned that

Greetings to the list, I was trying to estimate spatial error model in R, somehow I got the message below. Would you please help me with it? Many thanks in advance. Error in solve.default(asyvar, tol = tol.solve) : system is computationally singular: reciprocal condition number = 5.6964e-18 Regards, Dong

Dear all, I am currently facing a problem related to the spatial autocorrelation of a sample of stations; these stations supply weekly data for a fixed time-window during the year (namely, 4-6 months per year). For this reason I'm trying to use the R package 'spdep' (specifically Moran's I) in order to get rid of it. Does anyone know how is it possible (if it is...) to

Dear List, I have some problem with my simulation code. Here is output from R: > sim.sp <- function(data,CM,n,N) + { + C <- matrix(rep(NA,N),ncol=1) + for(i in 1:N) + { + j <- n + xx <- which(colSums(CM[j,])==1) + V <- names(xx) + V <- paste(V, collapse="+") + V <- paste("SBA~", V) + rd <- round(nrow(data)*(2/3)) + d <-

Hi, I have collected data on trees from 5 forest plots located within the same landscape. Data within the plots are spatially autocorrelated (calculated using Moran's I). I would like to do a ANCOVA type of analysis combining these five plots, but the assumption that there is no autocorrelation in the residuals is obviously violated. Does anyone have any ideas how to incorporate these spatial

I'm trying to use the spdep package to calculate this: y = rho W y + e I don't want to use explanatory variables, just the lag from the dependent variable. How would I code this?

Ciao, ho aperto con R un file di classe data frame con 15000 righe e 29 colonne. Nella console però sono visualizzate solo la prime e l'ultima colonna e le ultime 8000 righe circa. E' possibile una visualizzazione completa? Grazie Sabrina [[alternative HTML version deleted]]

Dear List, I have got error message when I run the R-code. Can anyone has a suggestion? v.code <- df.bm7[,c(10:31)]; v.code[1:3,] names(v.code) CM = v.code # variable binomial code sim.sp <- function(data,CM,n,N) { C <- matrix(rep(NA,N),ncol=1) for(i in 1:N) { j <- n xx <- which(colSums(CM[j,])==1) V <- names(xx) V <- paste(V,