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Help to generate diagnostic plots from spatial regression
2 messages · Ram Pandit, Roger Bivand
On Wed, 4 Feb 2009, Ram Pandit wrote:
Dear all, Pardon me for my limited knowledge in R. I am trying to generate the plot of fitted value vs. residual from a spatial regression like in ordinary regression, if possible. I tried the followings but did not get what I want (different diagnostic plots that can be generated by plot() in linear regression). Any hints will be appreciated.
library(spdep)
fit1<-lagsarlm(y~x1+x2+x3,data=data1,weight file,zero.policy=TRUE) # I defined the appropriate data file and weight file summary(fit1) library(car) plot(fit1) # it gives me following error Error in plot.window(...) : need finite 'xlim' values In addition: Warning messages: 1: In min(x) : no non-missing arguments to min; returning Inf 2: In max(x) : no non-missing arguments to max; returning -Inf 3: In min(x) : no non-missing arguments to min; returning Inf 4: In max(x) : no non-missing arguments to max; returning -Inf # when I do- plot(fit1$fit, fit1$res) # it gives the plot of fit1$fit vs. Index ( i guess the observation number)
There is no plot() method for an object of class "sarlm", so you get sent to the default method. For what it's worth, you could try: plot(fit1$lm.target) which will use the correct method, but disregarding the spatial coefficient and using an inappropriate hat matrix. There is a paper by Haining describing diagnostic plots for spatial regression models, but no-one has implemented them. Roger
Thank you. Ram Pandit
Roger Bivand Economic Geography Section, Department of Economics, Norwegian School of Economics and Business Administration, Helleveien 30, N-5045 Bergen, Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43 e-mail: Roger.Bivand at nhh.no