qfa (version 4.0)

sqr.fit: Spline Quantile Regression (SQR)

Description

This function computes spline quantile regression (SQR) solution from response vector and design matrix. It uses the FORTRAN code rqfnb.f in the "quantreg" package with the kind permission of Dr. R. Koenker.

Usage

sqr.fit(
  X,
  y,
  tau,
  spar = 1,
  d = 1,
  weighted = FALSE,
  mthreads = TRUE,
  ztol = 1e-05
)

Value

A list with the following elements:

coefficients

matrix of regression coefficients

crit

sequence critera for smoothing parameter select: (AIC,BIC,SIC)

np

sequence of number of effective parameters

fid

sequence of fidelity measure as quasi-likelihood

nit

number of iterations

Arguments

X

design matrix (nrow(X) = length(y))

y

response vector

tau

sequence of quantile levels in (0,1)

spar

smoothing parameter

d

subsampling rate of quantile levels (default = 1)

weighted

if TRUE, penalty function is weighted (default = FALSE)

mthreads

if FALSE, set RhpcBLASctl::blas_set_num_threads(1) (default = TRUE)

ztol

zero tolerance parameter used to determine the effective dimensionality of the fit