nlrq.control: Set control parameters for nlrq

In quantreg: Quantile Regression

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

maxiter	maximum number of allowed iterations
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
InitialStepSize	Starting value in 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.
big	a large scalar
eps	tolerance for convergence of the algorithm
beta	a shrinkage parameter which controls the recentering process in the interior point algorithm.

See Also

nlrq

quantreg documentation built on Oct. 22, 2024, 5:07 p.m.