variance covariance matrix of parameter estimate using nlrq

classic Classic list List threaded Threaded
2 messages Options
Reply | Threaded
Open this post in threaded view
|

variance covariance matrix of parameter estimate using nlrq

kate-26
In "lm" command, we can use "vcov" option to get variance-covariance matrix. Does anyone know how to get variance-covariance matrix in nlrq?

Thanks,

Kate
        [[alternative HTML version deleted]]

______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Reply | Threaded
Open this post in threaded view
|

Re: variance covariance matrix of parameter estimate using nlrq

RKoenker
mea culpa:  I've not written an extractor for this, so you have to do

        f <- nlrq(whatever)
        g <- summary(f)
        g$cov

Note that this is computed by resampling so it varies somewhat  
depending on the seed.

url:    www.econ.uiuc.edu/~roger            Roger Koenker
email    [hidden email]            Department of Economics
vox:     217-333-4558                University of Illinois
fax:       217-244-6678                Champaign, IL 61820


On Aug 11, 2008, at 4:12 PM, kate wrote:

> In "lm" command, we can use "vcov" option to get variance-covariance  
> matrix. Does anyone know how to get variance-covariance matrix in  
> nlrq?
>
> Thanks,
>
> Kate
> [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

______________________________________________
[hidden email] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.