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

[Roger Bivand]

On Wed, 12 Apr 2017, Qiuhua Ma wrote:

> Is this the link to the package?
>
> https://r-forge.r-project.org/R/?group_id=182

Yes, and:

install.packages("spdep", repos="http://R-Forge.R-project.org")

should work. But do try sphet::spreg() too, it is more flexible than the 
older spdep GM functions.

Roger

>
> Chelsea
>
> On Tue, Apr 11, 2017 at 10:59 PM, Qiuhua Ma <qiuhuanihao at gmail.com> wrote:
>
>> 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
>>>>
>>>>         [[alternative HTML version deleted]]
>>>>
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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
>>>
>>
>>
>

-- 
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