similar to: Moran I for very large data set

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

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,

Hi- I would like to assign distance classes (lags) to the moran''s I test in R. I don¹t have equally spaced points since I was mapping shrubs across a landscape (vs. an experiment or survey in a grid). I somehow need to select points based on the distances in the distance matrix (i.e., I need to select all pairs of points that occur 0-25 m from each other, 25-50 m, etc...). Does

Hi, I am a new student to R and I was hoping someone could help me with the error message I keep getting when I try to use the nb2listw() function. I have 45 sites and I want to get an autocorrelation value for sites within 1000m of each other. coords<-cbind(EAST,NORTH) coords<-as.matrix(coords) nb1000<-dnearneigh(coords,0,1000,longlat=TRUE) then when I try to run the

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! Using apt I have deb http://wine.sourceforge.net/apt/ binary/ deb-src http://wine.sourceforge.net/apt/ source/ This used to work. Now dselect comes up with wine depends on libxxf86dga1 libxxf86dga1 does not appear to be available How is this? What to do? pi

hi,friends, we all know that moran's I index and Geary'C index can be used to test spatial autocorrelation in both the area data and point data, but i only can find something on how to calculate on the data of area, and can't find the methods to perform it on the point data, could anybody give me some information, thanks in advance! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of

Hi I am trying to add density lines to multiple histograms created using R. I have managed to get all 18 lines on the last histogram in the series, however, i cannot figure out how to get each line appear on the correct histogram plot. I know in Matlab there is a hold function, is there something similar in R? the following is the code i have used to get mutiple plots and then add all the

Dear R-developers, I finally got around to install R 1.1.0 but had problems at the `make check' stage. After compiling the released R 1.1.0 version the `make check' stage stopped while checking the examples in base. There was some problem with the quantile function and the check stopped complaining that NA's are not allowed. But I assume that this problem is already known because

I have had a bunch of issues getting reverse proxy running with apache properly, the main issue is with YP listings and having icecast list the revproxy mount at port 80 rather than the icecast one at port 8000. Unfortunately, I /need/ some sort of http server on port 80 - and I know apache the best. That being said, if you know the mounts you want to reverse proxy, its not an arduous exercise

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

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Hi, I have asterisk running a single T1 card with a connection to a nortel CS 1000. All calls to extensions, local and long distance are working just fine. My issue is this: The nortel CS 1000 supports connections to and intercom system that is just line level audio to speakers. When my PRI tries to call this "extension" it is never answered so my AGI never runs to play a message

Okay, but you’d have to be able/willing to employ a dedicated IP to that, plus run Icecast as root. What are the negative technical implications of running icecast on port 8000 (suitable for most users) and then running a reverse proxy to accommodate public wifi with port restrictions? > On Apr 8, 2019, at 3:31 PM, Yahav Shasha <yahav.shasha at gmail.com> wrote: > > Just bind

Hi all, I've been struggling learning R and need to turn to the list again. I've got a dataset (comma-delimited file) with the following fields: recid, latitude, longitude, population, dwelling and age. For each observation, I'd like to calculate the total number of people and dwellings and average age within 2 k.m. Distance could be Euclidean, however, a proper distance

Hi! I'm using GLM, LDA and NaiveBayes for binomial classification. My training set is 70 rows long with 32 features, and my test set is 30 rows long with 32 features. Using Naive Bayes, I can train a model, and then predict the test set with it like so: ass4q1.dLDA = lda(ass4q1.trainSet[,1]~ass4q1.trainSet[,2:3]) table(predict(ass4q1.dNB, ass4q1.testSetDF[,2:3]), ass4q1.testSetDF[,1])

I called Digium today and hear some neat nifty music on hold that isn't included with Asterisk.. anyone have any idea what it is.. and where I can get it (if it's in the public domain)?

Anyone like to comment on why I'm receiving this evening 100's of emails from last July, and August that were posted to the wine-users list. All a bit weird. Nigel.