[R-sig-Geo] variance-covariance matrix for GMerrorsar

[Qiuhua Ma]

Thanks for your quick reply. You are right. Marginal wtp should take into
account rho for spatial lag model.

I still would like to use GMerrorsar. Can you please send me the source
package?

Best,

Chelsea

On Tue, Apr 11, 2017 at 7:54 AM, Roger Bivand <Roger.Bivand at nhh.no> wrote:

> On Tue, 11 Apr 2017, Qiuhua Ma wrote:
>
> Dear list,
>>
>> I want to use bootstrapping to derive confidence intervals for marginal
>> wtp after GMerrorsar command.
>>
>> It works for stsls since covariance matrix is directly available. However,
>> I cannot find covariance matrix for GMerrorsar.
>>
>> For example, the following code works for stsls:
>>
>> model1.beta <- coef(model1)
>>
>> model1.vcov <- summary(model1)$var
>>
>> model1.sim <- rmultnorm(10000, mu = model1.beta, vmat = model1.vcov)
>>
>> model1.mwtp <- model1.sim * Pbar
>>
>> model1.ci <- apply(model1.mwtp, 2, quantile, c(0.025, 0.975))
>>
>
> The DGP for this model is (I - \rho W)^{-1} (X \beta + e), so I'm in geat
> doubt about whether your proposal is correct (model1.vcov is has one more
> row and column than X has columns, so including \rho); the first element of
> model1.beta is \rho.
>
>
>>
>> when I apply the same code for GMerrorsar:
>>
>>
>> model2.beta <- coef(model2)
>>
>> model2.vcov <- summary(model2)$var
>>
>>
>> model2.vcov
>>>
>>
>> NULL
>>
>>
>> How can I obtain covariance matrix for GMerrorsar?
>>
>> Reading the code, you'll see where the matrices occur. Running under
> debug, you can assign the outside the environment of the function if you
> like (use <<- ). I've added a vcov component in the returned object (source
> on R-Forge, I can send a source package or a Windows binary package).
>
> You should also look at sphet::spreg, which does return a var component.
> Please note that you should think of the DGP first and foremost, the coef
> and var may return the values for what you are treating as nuisance parts
> of the model. Getting the distribution of the willingess to pay also
> probably involves them and their variability.
>
> Have you considered getting the WTP marginal from a Bayesian approach?
>
> Hope this helps,
>
> Roger
>
>
>
>> Chelsea
>>
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>>
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>>
> --
> Roger Bivand
> Department of Economics, Norwegian School of Economics,
> Helleveien 30, N-5045 Bergen, Norway.
> voice: +47 55 95 93 55; e-mail: Roger.Bivand at nhh.no
> Editor-in-Chief of The R Journal, https://journal.r-project.org/index.html
> http://orcid.org/0000-0003-2392-6140
> https://scholar.google.no/citations?user=AWeghB0AAAAJ&hl=en
>

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