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Help for spdep package

2 messages · Saman Monfared, Roger Bivand

Original
Saman Monfared
# 
Dear all.
I try to fit conditional auto regressive models (CAR and  SAR) in package spdep.
Also, I have fitted some other models like GLM, Empirical Bayes and ...

My program to CAR and SAR is:

esar1f1 <- spautolm(IMR.m~ 0+PCFP+Sup+B.F,data =data1,
 listw=nb2listw(nb6, style="W"), family="SAR", method="full", verbose=TRUE)

summary(esar1f1)

esar1f2 <- spautolm(IMR.m~ 0+PCFP+Sup+B.F,data =data1,
listw=nb2listw(nb6, style="W"), family="CAR", method="full", verbose=TRUE)
Call:
spautolm(formula = IMR.m ~ 0 + PCFP + Sup + B.F, data = data1,
    listw = nb2listw(nb6, style = "W"), family = "SAR", method = "full",
    verbose = TRUE)

Coefficients:
      PCFP        Sup        B.F     lambda
 0.1711382 -0.2262700  0.2414336 -1.7946991

Log likelihood: -56.24405


What is lambda?? I couldn't find a good refrences to understand tese model!!!
How can I predict this model for new data??
How can I cross validate results of CAR and SAR??
Roger Bivand
#
On Tue, 18 Dec 2012, Saman Monfared wrote:

            

      
      
      
    

        
See the help page (lambda is said to be the ML autoregressive coefficient 
about half way down), and certainly read Waller & Gotway (it may be that 
they term the spatial coefficient rho, but lambda is used here for 
consistency with errorsarlm()).

            

      
      
      
    

        
There are no predict methods provided - but analysis of the model will 
show that \hat{y} is X \beta, isn't it?

            

      
      
      
    

        
They are not nested processes, but as Clif & Ord, Ripley and the others 
show, a CAR and a SAR may be expressed in terms of one-another.

By the way, your lambda may me maxing out at the bottom of its range, so 
be careful, very strong negative autocorrelation is very unlikely.

Roger