On Wed, 25 Aug 2004, Jeff Hollister wrote: > Howdy All, > > I am looking for some good tutorials (books, websites, whatever) for > calculating/testing for Spatial Autocorrelation using R. > > Specifically, I am wanting to test for autocorrelation of a number of > variables measured at a set of discrete locations. >
>From your signature line, "Environmental Data", spatial autocorrelation could mean a number of things, depending on whether the variables could be measurements of a continuous surface of values at your discrete locations, or whether the discrete locations are "spatial entities" formed as areal aggregations of some kind. Since you mention spdep below, I'm assuming that the data you are working on refer to "spatial entities", for which Moran's I would be a reasonable choice of test. If the variable of interest isn't of this form, then other packages are more relevant (see R spatial projects link below). > Up to this point I have been exploring the "spdep" package and I can get > "moran.test" to work, but I am concerned that somewhere along the line I > may not be doing things correctly. Hence my request for a tutorial so > that I may brush up on my autocorrelation basics, specifically > autocorrelation with R, and reassure myself that the results I am > getting aren't bogus. Admittedly, the help page for moran.test() simply refers to Cliff, A. D., Ord, J. K. 1981 Spatial processes, Pion, p. 21 as the original source, and the "sids" vignette (see the foot of the output of help(package=spdep) to locate it on your system) is incomplete. My guess is however that if your data are for "spatial entities", theb constructing a sensible neighbour weights is at least 75% of the work - you will also see this in Virgilio Gómez-Rubio's "DCluster" package, and the existing "sids" vignette does cover that a little. Completing and improving this vignette is on my TODO list. If you are unsure of the result, and want to stay within the R framework, consider calculating Moran's I using DCluster, or gearymoran() in "ade4". Beyond that, you could access the GeoDa software (Windows, not R) and documentation at http://sal.agecon.uiuc.edu/csiss/geoda.html, the site also housing the R spatial projects web pages: http://agec221.agecon.uiuc.edu/csiss/Rgeo/ Please contact me off-list, or on the R-sig-geo list if you feel that would help. Best wishes, Roger Bivand > > Thanks in advance for any suggestions! > > Jeff Hollister > > ***************************************************** > Jeffrey William Hollister > Ph.D. Candidate > Environmental Data Center > Department of Natural Resources Science > University of Rhode Island > office: (401) 874 5054 > fax: (401) 874 4561 > cell: (401)556 4087 > http://www.edc.uri.edu/personal/jeff/home/jwh_cv_full.htm > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > -- Roger Bivand Economic Geography Section, Department of Economics, Norwegian School of Economics and Business Administration, Breiviksveien 40, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 93 93 e-mail: [EMAIL PROTECTED] ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html