Re: [R] spatial probit/logit for prediction
Hi Robb, the gamboost() function in package `mboost' may help. The details are described in @article{Kneib+Hothorn+Tutz:2009, author = {Thomas Kneib and Torsten Hothorn and Gerhard Tutz}, title = {Variable Selection and Model Choice in Geoadditive Regression Models}, journal = {Biometrics}, year = {2009}, note = {Accepted} } (preprint available from http://epub.ub.uni-muenchen.de/2063/) Best wishes, Torsten __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] spatial probit/logit for prediction
Freeman, Robert rfreeman at emcc.edu writes: I am wondering if there is a way to do a spatial error probit/logit model in R? I can't seem to find it in any of the packages. I can do it in MATLAB with Gibbs sampling, but would like to confirm the results. Ideally I would like to use this model to predict probability of parcel conversion in a future time period. This seems especially difficult in a binary outcome model setting. There are no such functions (as far as I know) in any package on CRAN for a spatial weights matrix based approach based say on contiguities. You could consider asking on the R-sig-geo list, and/or reviewing http://leg.ufpr.br/Rcitrus/, which may prove helpful (especially if you know Portuguese). Roger __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] spatial probit/logit for prediction
Hello all, I am wondering if there is a way to do a spatial error probit/logit model in R? I can't seem to find it in any of the packages. I can do it in MATLAB with Gibbs sampling, but would like to confirm the results. Ideally I would like to use this model to predict probability of parcel conversion in a future time period. This seems especially difficult in a binary outcome model setting. Does anyone have any guidance on this aspect? Thanks. Robb __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.