linear against nonlinear alternatives - quantile regression

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@> 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
                        
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-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
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