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copulaSFM  

Copula-Based Stochastic Frontier Models
View on CRAN: Click here


Download and install copulaSFM package within the R console
Install from CRAN:
install.packages("copulaSFM")

Install from Github:
library("remotes")
install_github("cran/copulaSFM")

Install by package version:
library("remotes")
install_version("copulaSFM", "0.2.0")



Attach the package and use:
library("copulaSFM")
Maintained by
Woraphon Yamaka
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-02-18
Latest Update: 2026-02-18
Description:
Provides estimation procedures for copula-based stochastic frontier models for cross-sectional data. The package implements maximum likelihood estimation of stochastic frontier models allowing flexible dependence structures between inefficiency and noise terms through various copula families (e.g., Gaussian and Student-t). It enables estimation of technical efficiency scores, log-likelihood values, and information criteria (AIC and BIC). The implemented framework builds upon stochastic frontier analysis introduced by Aigner, Lovell and Schmidt (1977) <doi:10.1016/0304-4076(77)90052-5> and the copula theory described in Joe (2014, ISBN:9781466583221). Empirical applications of copula-based stochastic frontier models can be found in Wiboonpongse et al. (2015) <doi:10.1016/j.ijar.2015.06.001> and Maneejuk et al. (2017, ISBN:9783319562176).
How to cite:
Woraphon Yamaka (2026). copulaSFM: Copula-Based Stochastic Frontier Models. R package version 0.2.0, https://cran.r-project.org/web/packages/copulaSFM. Accessed 04 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:28), 0.1.0 (2026-02-18 20:00)
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Complete documentation for copulaSFM
Functions, R codes and Examples using the copulaSFM R package
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