sfn.control: Set Control Parameters for Sparse Fitting

In quantreg: Quantile Regression

Set Control Parameters for Sparse Fitting

Description

Auxiliary function for setting storage dimensions and other parameters rq.fit.sfn[c]

Usage

sfn.control(nsubmax = NULL, tmpmax = NULL, nnzlmax = NULL, cachsz = 64, 
	small = 1e-06, maxiter = 100, warn.mesg = TRUE)

Arguments

nsubmax	upper bound for dimension of lindx
tmpmax	upper bound for dimension of tmpvec
nnzlmax	upper bound for non-zero entries of L stored in lnz, including diagonal
cachsz	size of cache in kbytes on target machine
small	convergence tolerance for interior point algorithm
maxiter	maximal number of interior point iterations.
warn.mesg	logical flag controlling printing of warnings.

Details

Sparse fitting requires a number of temporary storage arrays whose size depends on problem specific features in somewhat mysterious ways, parameters controlling these sizes and some other fitting aspects can be controlled by specifying elements of this control object.

Value

List with components named as the arguments given above.

Author(s)

Roger Koenker

See Also

See Also rq.fit.sfn

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