Copula Based Stochastic Frontier Quantile Model R package copulaSQM version 0.1.0 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. Software Imports: ald, VineCopula, stats, graphics, MASS Woraphon Yamaka <woraphon.econ@gmail.com> Comprehensive R Archive Network (CRAN) Woraphon Yamaka [aut, cre], Paravee Maneejuk [aut], Nuttaphong Kaewtathip [aut] GPL-3 2026-03-04 application/tgz https://CRAN.R-project.org/package=copulaSQM doi:10.32614/CRAN.package.copulaSQM