[R] covariate data errors

[Prof Brian Ripley]

Do you mean correlations in the *errors*?  The residuals are always 
correlated.  What does this have to do with your subject line -- it is 
errors in the dependent variable I think you mean?

If you have correlated errors, you should be using generalized least
squares not least squares or weighted least squares.  (That is covered in
all good books on regression: I don't know your level, but Seber's has a
comprehensive account.)  There are several R functions to fit GLS,
including gls(nlme) and lm.gls(MASS).


On Thu, 12 Jun 2003, 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
> 
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
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