[R] model II regression - how do I do it?

[Michael Grant]

Dear Danilo:

Here is one approach with the formal reference being:

Computational Statistics & Data Analysis 23 ( 1997 ) 355-372
COMPUTATIONAL
STATISTICS
& DATA ANALYSIS
Generalization of the geometric mean
functional relationship
Norman R. Draper, Yonghong (Fred) Yang
Department of Statistics, 1210 West Dayton Street, Madison, WI 53706-1685, USA
Received February 1995; revised February 1996

Here is the S version of their program (for two predictor variables):

Appendix

The Splus code has been used to specify the weight functions and fit the model:
Specify the weight function:
weight < - function(y,x 1,x2,b0,b 1,b2)
{
pred <-b0+b l*x 1 ÷b2*x2
parms <-abs(b 1"b2)^(1/3)
(y-pred)/parms
}
Fit the model
gmfit < -nls(~weight(y,x 1,x2,b0,b 1,b2),
observe,list("starting value"))


Hope this helps.
MCG

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Danilo Muniz
Sent: Friday, August 29, 2008 11:37 AM
To: r-help at r-project.org
Subject: [R] model II regression - how do I do it?

I need to do a model II linear regression, but I could not find out how!!

I tryed to use the lm function, but I did not discovered how to specify the
model (type I or type II) to the function... could you help me?

-- 
Danilo Muniz
[Gruingas Abdiel]

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