[R] covariate data errors

[Paul, David A]

I have found "Mixed Effects Models in S and Splus" by 
Drs. Pinheiro and Bates to be enormously helpful.
I highly recommend the book - it contains excellent
examples.

Best,
  david paul

-----Original Message-----
From: Prof Brian Ripley [mailto:ripley at stats.ox.ac.uk] 
Sent: Friday, June 13, 2003 2:54 AM
To: Andy Jacobson
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] covariate data errors


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)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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