similar to: Spatial error model estimation

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, just to put it in a simple way: i read.csv from csv file to create a gdata then, create array gdata34 however, when making a loop for assigning gdata34[1,m]<-gdata[m,4], this is what happen gdata[1,4] 's real value is 10354, however, the gdata34[1,4] turns to be 883 then i checked the type: gdata[1,4] is integer, while gdata34[1,4] is double. Can any one give me some help

Dear all, Has someone implemented in R (or any other language) Knol DL, ten Berge JMF. Least-squares approximation of an improper correlation matrix by a proper one. Psychometrika, 1989, 54, 53-61. or any other similar algorithm? Best regards Jens Oehlschl?gel Background: I want to factanal() matrices of polychoric correlations which have negative eigenvalue. I coded Highham 2002

Hello I've stumbled upon a problem for inversion of a matrix with large values, and I haven't found a solution yet... I wondered if someone could give a hand. (It is about automatic optimisation of a calibration process, which involves the inverse of the information matrix) code: ********************* > macht=0.8698965 > coeff=1.106836*10^(-8) >

Hi All, This is my R-version information:--- > version _ platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 7.1 year 2008 month 06 day 23 svn rev 45970 language R version.string R version 2.7.1 (2008-06-23) While calculating partial

enclosed a simple R script (and a data file, and the output) , with calls lda similar to the example with the iris data in the documentation. it is not working and i dont understand the error message. can anybody help me? i am using R 1.5.1 (2002.06.17) on debian woody stable. I would like to avoid updating now, because i want to keep the system in "stable". can somebody test, if the

Hi uRsers, when inverting a 2 by 2 matrix using solve, I encountered a error message: solve.default(sigma, tol = 1e-07) : system is computationally singular: reciprocal condition number = 1.7671e-017 and then I test the determinant of this matrix: 6.341393e-06. In my program, I have a condition block that whether a matrix is invertible like this: if(det(sigma)<1e-7) return NULL;

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

Hello, I have a question about multivariate Shapiro-Wilks test. I tried to analyze if the data I have are multivariate normal, or how far they are from being multivariate normal. However, any time I did >mshapiro.test(mydata) I get the message: Error in solve.default(R %*% t(R), tol = 1e-18) : system is computationally singular: reciprocal condition number = 5.38814e-021 I tried

Hi, I am trying to calculate mahalanobis distances for a matrix x with n*p variables. I am getting the following error: md2 <- mahalanobis(x, center, cov) Error in solve.default(cov, tol = tol.inv) : system is computationally singular: reciprocal condition number = 2.11165e-009 What does it means? Thank you so much for any help, Monica

Hello, I'm trying to run a lagsarlm (maximum likelihood estimation of a spatial lag model) in the spdep library ; but R gives following error message: Error in solve.default(inf, tol = tol.solve) : system is computationally singular: reciprocal condition number = 4.20137e-12 I get the same message when I try to run de lagsarlm with a bigger data set (4333 regions). The command

I have an R function defined as: f<-function(x){ return(dchisq(x,9,77)*((13.5/x)^5)*exp(-13.5/x)) } Numerically integrating this function, I observed a couple of things: A) Integrating the function f over the entire positive real line gives an error: > integrate(f,0,Inf) Error in integrate(f, 0, Inf) : the integral is probably divergent B) Increasing the interval of integration

Dear Sir, I am using the package pgmm you build in panel regression. However, I found that when T is 10, N=30, the error would show as following: system is computationally singular: reciprocal condition number But the similar code works well on Stata, so I wonder how I can optimize the algorithm, for example , the inverse matrix optimization ? And I have checked my data as well, no

Hi: First my apologies for cross-posting. A few days back I posted my queries ar R-sig-geo but did not get any response. Hence this post. I am working on two parcel-level housing dataset to estimate the impact of various variables on home sale prices. I created the spatial weight metrics in ArcGIS 10 using sale year of four nearest houses to assign weights.  Next, I ran LM tests and then ran

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

I get this error while computing partial correlation. *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* Why is it?Can anyone give me some idea ,how do i get rid it it? This is the function i use for calculating partial correlation. pcor.mat <- function(x,y,z,method="p",na.rm=T){ x <- c(x) y <- c(y)

something like ... > x<-c(1,2,3,0,5,6,0) > is.na(x[x==0])<-T > x [1] 1 2 3 NA 5 6 NA ~~~~~~~~~~~~~~~~ Robert Kinley ~~~~~~~~~~~~~~~~ [[alternative HTML version deleted]]

Dear all, I need to compute the ACF (autocorrel) of an AR6 process, given the values of its parameters (w1,w2,w3,w4,w5,w6). First, I notice that there is an error as soon as the sum of the wi equals 1 : "Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number = 1.00757e-18"

I'm trying to run the generalized least square approach for my 2-additive problem, unfortunately this error appeared. I have tried to figure out the error from the mailing list but couldn't find the solution. Any help is highly appreciated. This is my source code: >a1 <- c(76.18, 61.84, 60.4, 69.09) > a2 <- c(51.01, 50.39, 87.62, 52.03) > a3 <- c(80.08, 48.49, 90.86,

Dear R-help, I'm very sorry to ask 2 questions in a week. I am using the package 'crr' and it does exactly what I need it to when I use the dataset a. However, when I use dataset b I get the following error message: Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number =