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 <[email protected]> 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]] >> >> _______________________________________________ >> R-sig-Geo mailing list >> [email protected] >> https://stat.ethz.ch/mailman/listinfo/r-sig-geo >> >> > -- > Roger Bivand > Department of Economics, Norwegian School of Economics, > Helleveien 30, N-5045 Bergen, Norway. > voice: +47 55 95 93 55; e-mail: [email protected] > 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 > [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-geo
