copulaSQM: Copula Based Stochastic Frontier Quantile Model

Provides estimation procedures for copula-based stochastic frontier quantile models for cross-sectional data. The package implements maximum likelihood estimation of quantile regression models allowing flexible dependence structures between error components through various copula families (e.g., Gaussian and Student-t). It enables estimation of conditional quantile effects, dependence parameters, log-likelihood values, and information criteria (AIC and BIC). The framework combines quantile regression methodology introduced by Koenker and Bassett (1978) <doi:10.2307/1913643> with copula theory described in Joe (2014, ISBN:9781466583221). This approach allows modeling heterogeneous effects across quantiles while capturing nonlinear dependence structures between variables.

Version:	0.1.0
Imports:	ald, VineCopula, stats, graphics, MASS
Published:	2026-03-04
DOI:	10.32614/CRAN.package.copulaSQM (may not be active yet)
Author:	Woraphon Yamaka [aut, cre], Paravee Maneejuk [aut], Nuttaphong Kaewtathip [aut]
Maintainer:	Woraphon Yamaka <woraphon.econ at gmail.com>
License:	GPL-3
NeedsCompilation:	no
Materials:	README
CRAN checks:	copulaSQM results

Documentation:

Reference manual:

copulaSQM.html , copulaSQM.pdf

Downloads:

Package source:	copulaSQM_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

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