Thanks, Roger. And thanks for alerting me to the possible issues with the
coefficient covariance matrix. For my immediate purposes, this yields
plausible results.

On Sun, Jul 3, 2011 at 10:54 AM, Roger Bivand <Roger.Bivand@nhh.no> wrote:

> On Sat, 2 Jul 2011, Jason Sorens wrote:
>
>  I'm interested in testing linear combinations of coefficients after models
>> like spautolm, errorsarlm, and lagsarlm in the spdep package. I'm used to
>> using "anova" for this, but the anova.sarlm implementation doesn't seem to
>> permit it straightforwardly. For instance, if I wanted to testing
>> something
>> like b_1-.25*b_2=0, how would I go about doing that?
>>
>
> See the linearHypothesis() methods in the car package. I think that, after
> someone has checked that all is as it should be, sarlm objects could get a
> vcov() method, which they do not have now. These work formally, but are not
> checked:
>
> library(car)
> library(spdep)
> example(columbus)
> lmobj <- lm(CRIME ~ HOVAL+INC, data=columbus)
> linearHypothesis(lmobj, "HOVAL-INC=0", test="Chisq")
> lagobj <- lagsarlm(CRIME ~ HOVAL+INC, data=columbus,
>  listw=nb2listw(col.gal.nb))
> linearHypothesis(lagobj, "HOVAL-INC=0", test="Chisq",
>  vcov.=lagobj$resvar[2:5,2:5])
> errobj <- errorsarlm(CRIME ~ HOVAL+INC, data=columbus,
>  listw=nb2listw(col.gal.nb))
> linearHypothesis(errobj, "HOVAL-INC=0", test="Chisq",
>  vcov.=errobj$resvar[2:5,2:5])
>
> Please do check that this is an appropriate use of the returned values when
> fitted using eigenvalues. Other steps would be needed when a (mixed)
> numerical Hessian is used to approximate the variance/covariance matrix of
> the coefficients. Then a vcov() method could be added for sarlm objects, but
> it needs caution and analysis.
>
> Hope this helps,
>
> Roger
>
>
>
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> --
> Roger Bivand
> Department of Economics, NHH Norwegian School of Economics,
> Helleveien 30, N-5045 Bergen, Norway.
> voice: +47 55 95 93 55; fax +47 55 95 95 43
> e-mail: Roger.Bivand@nhh.no
>
>

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