copulaSQM

Description

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.

Downloads

CRAN Check Status

Check History

LaTeX errors when creating PDF version.
This typically indicates Rd problems.
LaTeX errors found:

Dependency Network

R Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Mar 4, 2026. Releases before tracking aren’t shown.