[R] nlrq {quantreg}

[Roger Koenker]

The model _is_ linear in parameters, after the log transformation of  
the response, so
you don't need nlrq.  If you really want something like:

	y = exp(a + b x)   +  u

then you need to make a token effort to look at the documentation.    
Here is another
example:

x <- exp(rnorm(50))
y <- exp(1 + .5*x) + rnorm(50)

nlrq(y ~ exp(a  + b * x), start = list(a = 2, b = 1))
Nonlinear quantile regression
    model:  y ~ exp(a + b * x)
     data:  parent.frame
      tau:  0.5
deviance:  15.39633
         a         b
1.0348673 0.4962638


Roger Koenker
rkoenker at illinois.edu




On Oct 16, 2011, at 3:59 AM, Julia Lira wrote:

>
> Dear all,
> I sent an email on Friday asking about nlrq {quantreg}, but I  
> haven't received any answer.
> I need to estimate the quantile regression estimators of a model as:  
> y = exp(b0+x'b1+u). The model is nonlinear in parameters, although I  
> can linearise it by using log.When I write:
> fitnl <- nlrq(y ~ exp(x), tau=0.5)
> I have the following error: Error in match.call(func, call = cll) :  
> invalid 'definition' argument
> Is there any way to estimate this model, or should I accept the  
> following change:
> fitnl <- rq(log(y) ~ x, tau=0.5) ?
> Thanks in advance!
> Best,
> Julia 		 	   		
> 	[[alternative HTML version deleted]]
>
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