similar to: problem with nb2listw

Hi, I am trying to calculate Moran's I test for the residuals for a regression equation, but I have trouble converting my coordinates into nb format. I have used the dnearneigh() funtion now with an arbitrarily high upper distance to make it include all plots. However, when I do the lm.morantest() I get a Moran's I value which is the same as the expected value and a P-value of 1. I

Hi, I was wondering if someone could help me answer a question that is bound to come up in my Master's defense. I'm using AIC to select models and my question is how do I know that the models I developed a priori contain the 'best' models in the system. How do I not know that some models which I didn't include aren't actually the 'best' model?? Thanks so much

hello, I want to do a test for spatial correlation. I tried it with geary.test() but I don't understand the required input. x= a numeric vector the same length as the neighbours list in listw (my sampled data, I assume) listw= a listw object created for example by nb2listw (well when I check nb2listw() I get to "neighbours - an object of class nb" - but I couldn't figure

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

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 <-

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,

Hi, I'm currently trying to calculate local Getis-Ord Gi* statistics for a 169x315 cell matrix of temperature values, below is the code I currently have (diffc is the data vector I am removing NaN values from, and I am moving said values to diffD; -999 represents NaN values; id contains ID values for cells I want to use in the calculation, which I already know to contain 25064 values):

Hi, I have a number of spatial weight files and using Roger Bivand's spdep, I would like to 1. Convert them into neighbor lists using 2. Convert the neighbor lists into spatial weights For a given file, the syntax would be mygal_nb1 <- read.gal("mygalfile1", override.id = TRUE) myweight1 <- nb2listw(mygal_nb1) I have mygalfile[i] with i from 1 through to 6 and would like to

Can someone tell me what an object of class lm returned by lm means? I assumed it mean the regression model - but I'm not sure how to enter this in. I have tried y~a+b but this is not working. I have also tried saving the regression results and entering these, but again this is incorrect. This language is from the following: lm.LMtests(model, listw, zero.policy=FALSE,

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I get tables with millions of rows. For plotting to a screen-size jpg, obviously just about 1000 points are enough. Instead of feeding plot() the original millions of rows, I'd rather shrink the original dataframe, using some kind of the following interpolation: -- split dataframe into chunks of N rows each, e.g. 1000 rows each -- compute average for each column -- issue one new row

Dear R users, I've written a loop to generate Moran's test (spdep package) on serval subsamples of a large dataset. See below a short example. My loop is working fine, however I would like to be able to store the test results as lines of a matrix, that I would latter be able to export as a dataset. My problem is that I'm not sure how I could do this using R. Any help will be much

Dear all, (Mac OS X 10.4.11, R 2.6.0) I have a quantitative dataset with a lot of Na?s in it. So many, that it is not possible to delete all rows with NA?s and also not possible, to delete all variables with NA?s. Is there a function for a principal component analysis, that can deal with so many NA?s. Thanks in advance Birgit Birgit Lemcke Institut f?r Systematische Botanik

Hello everybody, I would like to use the SpDep-package (especially the Local Moran index analysis and the Getis-Ord statistics) in R for analysing my data. However, I don't have x-y coordinates, but my data is in a distance matrix format. Is it possible to use the SpDep package with predefined distances as well instead of letting the program determining the distance itself by the function

dear R users, I have troubles performing Moran.I test as suggested on http://www.ats.ucla.edu/stat/r/faq/morans_i.htm my spatial data are longitude and lattitide of communities. The calculation of the inverse distance matrix according to the homepage (using my data) datAL <- read.csv2("C:\\Konvergenz AL.csv", header=T) ALdist <- as.matrix(dist(cbind(datAL$L?nge,

Dear all, I would like to calculate a Moran's I statistic using the moran function in the spdep package. The problem I'm having deals with how to create the listw object. My data stems from the area of social network analysis. I have list of poeple and for each pair of them I have a measure of their relationship strength. So my dataset looks like: Jim; Bob; 0.5 This measure of

Hi everyone, I have a matrix that contains 1000 replicates of a sample of a list of values. I want to group each row (row=replicate) into my defined bin ranges and then calculate the mean and stdev for each of the bin ranges (so I will have 1000 rows but ncol=number of bin ranges). I don't know how to group rows in a matrix matrix according to another vector (which is what I think I need to

Dear R user, I am using Sweave to write my reports with R code. Unlucly my code take a lot of time to run, and I don't want to run it multiple time, if possible, as I am still developping the tools. It seems that a sweave run does not save the enviroment at the end of the process, is there a way to avoid to lunch multiple time the same commands? maybe it could be possible to store chunck of

Hi the list, I am defining a new class MyClass. Shortly, I will submit a package with it. Before, I would like to know if there is a kind of "non official list" of what method a new S4 object have. More precisely, personnaly, I use 'print', 'summary' and 'plot' a lot. So for my new class, I define these 3 methods. Is there some other method that a R user can

Hi Everyone, I am doing a project based on "Spatially Lagged Predictor Variable Models", I would like to know which package in R would execute this model. Also, I am new to this field of spatial statistics. Any suggestions for a good book on spatial regression analysis would be appreciated. Thanks Again. Cheers Arun -- View this message in context: