[R] question

Roger Koenker rkoenker at illinois.edu
Thu Apr 25 03:02:05 CEST 2013

good usually means good relative to something else, in this case the comparison seems, as Michael
has already said, f0 <- rq(y ~ 1, tau = ?) and then one can compute the R1 version that I originally
suggested.  But since there is still no explicit way to evaluate this, it is all a bit pointless.

Roger Koenker
rkoenker at illinois.edu

On Apr 24, 2013, at 6:37 PM, R. Michael Weylandt wrote:

>> On Tue, Apr 23, 2013 at 2:54 PM, nafiseh hagiaghamohammadi
>> <n_hajiaghamohammadi2007 at yahoo.com> wrote:
>>> Hi
>>> I fit one  linear quantile regression with package quantreg and I want to
>>> khow this model is good or not.Is there method for checking it?
>>> Thanks your advice
>>  I ask this question because  there is 2 models,f0 and f1 in  (R1 <- 1 -
>> f1$rho/f0$rho ),
>> is it true?
>>  but I fit 1 model and I want to check goodness of fit for 1 model .
> Please keep your responses on list so you can get a quick reply even
> when I'm otherwise busy.
> I think you could -- for a rough and ready comparison -- compare
> against a constant (empirical quantile) model (not unlike how basic
> OLS models compare against the constant mean predictor)  but someone
> else might know if there's any subtleties about quantile regression
> that should be noted here.
> MW
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