R help - Feb 2008 - Multivariate Maximum Likelihood Estimation

Hi,

I am trying to perform Maximum Likelihood estimation of a Multivariate
model (2 independent variables + intercept) with autocorrelated errors of
1st order (ar(1)).

Does R have a function for that? I could only find an univariate option
(ar.mle function) and when writing my own I find that it is pretty
memory-consuming (and sometimes wrong) so there must be a better way.

Thanks,

KB

I get this message:

Error: could not find function "gls" (and also)
Error: could not find function "lm.gls"

Which package is that in?

Thanks,

KB
> Have you tried gls()?
>
>
> ------------------------------------------------------------------------
> ----
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature
> and Forest
> Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
> methodology and quality assurance
> Gaverstraat 4
> 9500 Geraardsbergen
> Belgium
> tel. + 32 54/436 185
> Thierry.Onkelinx at inbo.be
> www.inbo.be
>
> Do not put your faith in what statistics say until you have carefully
> considered what they do not say.  ~William W. Watt
> A statistical analysis, properly conducted, is a delicate dissection of
> uncertainties, a surgery of suppositions. ~M.J.Moroney
>
> -----Oorspronkelijk bericht-----
> Van: r-help-bounces at r-project.org [mailto:r-help-bounces at
r-project.org]
> Namens Konrad BLOCHER
> Verzonden: woensdag 6 februari 2008 12:12
> Aan: r-help at r-project.org
> Onderwerp: [R] Multivariate Maximum Likelihood Estimation
>
> Hi,
>
> I am trying to perform Maximum Likelihood estimation of a Multivariate
> model (2 independent variables + intercept) with autocorrelated errors
> of
> 1st order (ar(1)).
>
> Does R have a function for that? I could only find an univariate option
> (ar.mle function) and when writing my own I find that it is pretty
> memory-consuming (and sometimes wrong) so there must be a better way.
>
> Thanks,
>
> KB
>
> ______________________________________________
> R-help at r-project.org 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.
>

OK I got gls running but this is the error message that I got:
> gls_results <- gls(LnWRPK ~ LnWGDP+LnWYIELD,correlation = corAR1)
Error in switch(mode(x), "NULL" = structure(NULL, class =
"formula"),  :
  invalid formula

Google didn't give any results unfortunately.

Help! :)

Thanks,

KB
> Have you tried gls()?
>
>
> ------------------------------------------------------------------------
----
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
> Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
> Gaverstraat 4
> 9500 Geraardsbergen
> Belgium
> tel. + 32 54/436 185
> Thierry.Onkelinx at inbo.be
> www.inbo.be
>
> Do not put your faith in what statistics say until you have carefully
considered what they do not say.  ~William W. Watt
> A statistical analysis, properly conducted, is a delicate dissection of
uncertainties, a surgery of suppositions. ~M.J.Moroney
>
> -----Oorspronkelijk bericht-----
> Van: r-help-bounces at r-project.org [mailto:r-help-bounces at
r-project.org]
Namens Konrad BLOCHER
> Verzonden: woensdag 6 februari 2008 12:12
> Aan: r-help at r-project.org
> Onderwerp: [R] Multivariate Maximum Likelihood Estimation
>
> Hi,
>
> I am trying to perform Maximum Likelihood estimation of a Multivariate
model (2 independent variables + intercept) with autocorrelated errors
of
> 1st order (ar(1)).
>
> Does R have a function for that? I could only find an univariate option
(ar.mle function) and when writing my own I find that it is pretty
memory-consuming (and sometimes wrong) so there must be a better
way.
>
> Thanks,
>
> KB
>
> ______________________________________________
> R-help at r-project.org 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.
>