similar to: spatial correlation test

Hello, I'm new to R and to Spatial Analysis and got a problem trying to create a Spatial Weights Matrix. *I us the following code to create the Neighbourslist:* >library(maptools) >library(spdep) >library(rgdal) >location_County<- readShapePoly("....") >proj4string(location_County)<- CRS("+proj=longlat ellps=WGS84") >location_nbq<-

-----Original Message----- From: r-help-request at stat.math.ethz.ch [mailto:r-help-request at stat.math.ethz.ch] Sent: Tuesday, July 01, 2003 3:09 AM To: r-help at stat.math.ethz.ch Subject: R-help Digest, Vol 5, Issue 1 At 18:48 30/06/2003, Martin Wegmann wrote: >hello, > >I want to do a test for spatial correlation. >I tried it with geary.test() but I don't understand the

Dear Users: I have been trying to use the geary.test() function in *R*, but am having slight difficulty understanding how I am to apply it in my context. I have 2 matrices: 1) *n x p* matrix of *n* observations with *p* measurements each. It may be noted that this matrix has a spatial dimension to it, as the *n*observations are at different geographical locations on a map. 2) *n x n* spatial

Dear all, I would like to implement a spatial quantile regression using instrumental variable estimation (according to Su and Yang (2007), Instrumental variable quantile estimation of spatial autoregressive models, SMU economics & statistis working paper series, 2007, 05-2007, p.35 ). I am applying the hedonic pricing method on land transactions in Luxembourg. My original data set contains

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,

Dear All, We aim to remove the spatial structure of our data using Moran Eigen Vectors and spdep package . Our data has 3694 samples and 13 variables. The computer stop working after almost 4 days of processing (we found it emitting a sharp sound and with all colors on the screen. No wories, it was restared without problem!). And we are left with nothing: no result file was produced since 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 <-

Hi, I have a question on testing spatial autocorrelation on raster data including NA-values. In particular, I like to calculate Moran?s I and Geary?s C indices by using inverse distance weighting matrices. Calculating Moran?s I with moran.test works fine, because the function contains the option "na.action=na.pass". Unfortunately, the function geary.test does not contain this

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,

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

[This email is either empty or too large to be displayed at this time]

I have been running into difficulties with dispatching on an S4 class defined in the SparseM package, when the method calls are inside a function passed as the f= argument to optimize() in functions in the spdep package. The S4 methods are typically defined as: setMethod("det","matrix.csr", function(x, ...) det(chol(x))^2) that is within setMethod() rather than by name before

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 all, I am new here ,I attempted to use R to estimate the spatial Durbin (mixed) model,and mydata is a panel data form,and the matrix is generated by geoda software ,here is my Command and error,really hope your help ,thank you! #??gal library(spdep) w<- read.gal("E:/splm/zj.GAL",override.id=TRUE) ww<-nb2listw(w,zero.policy=TRUE) #???? library(foreign)

Hi all, I am sorry if this is a very basic quesion, but I have no experience with analyzing spatial data and could not find the right function/package quickly. Any hints would be much appreciated. I have a matrix of spatial point patterns like the one below and want to find the number of independent components (if that's the right term) in that matrix (or in that image). x=matrix(c(0,1,0,0,0,

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):

Hello I'm very new to R (which is excellent), so apologies if this has already been raised. In the spdep package, I'm trying to undertake an autoregressive mixed model using the lagsarlm function. This is working fine, but there does not appear to be a method of including an explanatory variable without it automatically being included as a lagged term. I'm after something along the

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

I want to do "moran's I test" in R language. I try to use "gearymoran" in Package "ade4","moran" in Package "spdep", and Moran.I in Package "ape". But I do not know how to do it because data format is different. My data: x y dbh 111.03 10.7 7 118.11 0.28 1.2 165.36 0.36 8.4

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