https://github.com/cran/quantreg
Revision 92269b50ae23297ededa6a58d77823e1302a6b8e authored by Roger Koenker on 06 June 2021, 16:10:02 UTC, committed by cran-robot on 06 June 2021, 16:10:02 UTC
1 parent e68bc7a
Tip revision: 92269b50ae23297ededa6a58d77823e1302a6b8e authored by Roger Koenker on 06 June 2021, 16:10:02 UTC
version 5.86
version 5.86
Tip revision: 92269b5
nlrq.control.Rd
\name{nlrq.control}
\alias{nlrq.control}
\title{ Set control parameters for nlrq }
\description{
Set algorithmic parameters for nlrq (nonlinear quantile regression function)
}
\usage{
nlrq.control(maxiter=100, k=2, InitialStepSize = 1, big=1e+20, eps=1e-07, beta=0.97)
}
\arguments{
\item{maxiter}{maximum number of allowed iterations}
\item{k}{the number of iterations of the Meketon algorithm to be calculated
in each step, usually 2 is reasonable, occasionally it may be helpful
to set k=1 }
\item{InitialStepSize}{ Starting value in \code{optim} to determine the step
length of iterations. The default value of 1 is sometimes too optimistic.
In such cases, the value 0 forces optim to just barely stick its toe in
the water.}
\item{big}{ a large scalar}
\item{eps}{ tolerance for convergence of the algorithm }
\item{beta}{ a shrinkage parameter which controls the recentering process
in the interior point algorithm. }
}
\seealso{ \code{\link{nlrq}} }
\keyword{ environment}
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