**From:** Andy Jacobson (*junkmail@mu.met.psu.edu*)

**Date:** Fri 13 Jun 2003 - 13:40:04 EST

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Message-id: <E19QfQ4-0004NQ-00@mu.met.psu.edu>

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

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**Next message:**Martin Maechler: "Re: [R] breaks"**Previous message:**Duncan Mackay: "RE: [R] covariate data errors"**Next in thread:**Bill.Venables@csiro.au: "RE: [R] covariate data errors"**Maybe reply:**Bill.Venables@csiro.au: "RE: [R] covariate data errors"**Reply:**John Fox: "Re: [R] covariate data errors"**Reply:**Duncan Mackay: "RE: [R] covariate data errors"**Reply:**Prof Brian Ripley: "Re: [R] covariate data errors"**Maybe reply:**Paul, David A: "RE: [R] covariate data errors"

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