Message-ID: <4A0451DD.9090105@googlemail.com>
Date: 2009-05-08T15:38:05Z
From: James Allsopp
Subject: Linear least squares fit with errors in both x and y values.
In-Reply-To: <OF9FEA5940.71E2AF5D-ON802575AF.0058463E-802575AF.005909CB@justice.ie>
Found an answer here, don't know if anyone's implemented it for R though.
www.iop.org/EJ/article/0022-3735/22/4/002/jev22i4p215.pdf
James
Gerard M. Keogh wrote:
> James,
>
> look up "errors in variables" models or "instrumental variable" models in
> econometrics.
>
> The statistics alternative is a "random effects" or "mixed effects" model
> which plugs the variation in the x's into a randomly varying parameter -
> these are available in R (?lmer or glmm - I think).
> Someone on the list much more knowledgeable than I about these will be able
> to give you some help if you ask a good question.
>
> Gerard
>
>
>
>
> James Allsopp
> <jamesaallsopp at go
> oglemail.com> To
> Sent by: r-help at r-project.org
> r-help-bounces at r- cc
> project.org
> Subject
> [R] Linear least squares fit with
> 07/05/2009 15:19 errors in both x and y values.
>
>
>
>
>
>
>
>
>
>
> HI,
> I'd like to perform a weighted linear least squares fit with R on data
> with varying errors on both vectors. I can do this with one axis using
> lm, but have no idea where to go from here. I've tried googling, but no
> idea. Any suggestions?
>
> Thanks,
> James
>
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