[Help-glpk] Re: reduced major axis regression (RMA) and allometric models using MathProg in GLPK

[Nigel Galloway]

Andrew,

Attached is xyacfs.mod which extends yacfs.mod to permit 
investigation of data which may have errors in x (XonY) or y 
(YonX). It adds a Weight parameter:

     When set to 1 the model produces best fit by least squares 
with all error in y and none in x (YonX);
     When set to zero the model produces best fit by least squares 
with all error in x and none in y (XonY);
     When set to 0.5 the model assumes equal error in x and y 
producing results similar to fitting by Reduced Major Axis Analysis.

Please add this to the examples section if you think it is uaseful.

Thanks,

Nigel



> ----- Original Message -----
> From: "Noli Sicad" <address@hidden>
> To: address@hidden
> Subject: reduced major axis regression (RMA) and allometric 
> models using  MathProg in GLPK
> Date: Fri, 23 Oct 2009 13:49:59 +1100
>
>
> Hi Nigel,
>
> Thanks for sharing your regression i.e. curve fitting examples using
> Mathprog in GLPK (cflsq.mod, qfit.mod and yacfs.mod).
>
> I think you have heard about RMA regression. Would be possible to have
> another example using  reduced major axis regression (RMA) using
> MathProg?
>
> Here are references:
>
> [R] test regression against given slope for reduced major axis 
> regression (RMA)
> http://finzi.psych.upenn.edu/R/Rhelp02a/archive/80841.html
>
> RMA http://www.bio.sdsu.edu/pub/andy/RMAmanual.pdf
>
> Thanks in advance.
>
> Regards, Noli

>


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