[R] linear against nonlinear alternatives - quantile regression

[David Winsemius]

I suppose this constitutes thread drift, but your simple example, Frank, made wonder if Rq() accepts a vector argument for tau. I seem to remember that Koencker's rq() does.. Normally I would consult the help page, but the power is still out here in Central Connecticut and I am corresponding with a less capable device. I am guessing that if Rq() does accept such a vector that the form of the nonlinearity would be imposed at all levels of tau.

-- 
David

On Nov 5, 2011, at 10:43 AM, Frank Harrell <f.harrell at vanderbilt.edu> wrote:

> Just to address a piece of this - in the case in which you are currently
> focusing on only one quantile, the rms package can help by fitting
> restricted cubic splines for covariate effects, and then run anova to test
> for nonlinearity (sometimes a dubious practice because if you then remove
> nonlinear terms you are mildly cheating).
> 
> require(rms)
> f <- Rq(y ~ x1 + rcs(x2,4), tau=.25)
> anova(f)  # tests associations and nonlinearity of x2
> 
> Frank
> 
> Julia Lira wrote:
>> 
>> Dear all,
>> 
>> I would like to know whether any specification test for linear against
>> nonlinear model hypothesis has been implemented in R using the quantreg
>> package. 
>> 
>> I could read papers concerning this issue, but they haven't been
>> implemented at R. As far as I know, we only have two specification tests
>> in this line: anova.rq and Khmaladze.test. The first one test equality and
>> significance of the slopes across quantiles and the latter one test if the
>> linear specification is model of location or location and scale shift. 
>> 
>> Do you have any suggestion?
>> 
>> Thanks a lot!
>> 
>> Best regards,
>> 
>> Julia
>>                         
>>    [[alternative HTML version deleted]]
>> 
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> 
> 
> -----
> Frank Harrell
> Department of Biostatistics, Vanderbilt University
> --
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