[R] covariate data errors

[John Fox]

Dear Anthony,

The gls (generalized least squares) function in the nlme package should do 
what you want. (I assume that your analysis leads you to expect an 
error-covariance matrix of a specific form with some free parameters to 
estimate.)

Generalized least squares estimation is a common topic in regression texts. 
You'll find a brief appendix on the subject from my R and S-PLUS Companion 
to Applied Regression, in the context of time-series regression, at 
<http://www.socsci.mcmaster.ca/jfox/Books/Companion/appendix-timeseries-regression.pdf>.

I hope that this helps,
  John

At 11:40 PM 6/12/2003 -0400, Andy Jacobson wrote:
>Greetings,
>
>         I would like to fit a multiple linear regression model in
>which the residuals are expected to follow a multivariate normal
>distribution, using weighted least squares.  I know that the data in
>question have biases that would result in correlated residuals, and I
>have a means for quantifying those biases as a covariance matrix. I
>cannot, unfortunately, correct the data for these biases.
>
>         It seems that this should be a straightforward task, but so
>much of the literature is concerned with the probability model in
>which the residuals are uncorrelated that I can't find a good
>reference.  So in order of importance, please, can someone point me to
>a definitive reference for least squares with correlated residuals,
>and is there a standard R package to handle this case?
>
>         Many thanks in advance,
>
>         Anthony

-----------------------------------------------------
John Fox
Department of Sociology
McMaster University
Hamilton, Ontario, Canada L8S 4M4
email: jfox at mcmaster.ca
phone: 905-525-9140x23604
web: www.socsci.mcmaster.ca/jfox