Probabilistic frontier regression models for binary type output data

DOI10.1080/02664763.2019.1597838OpenAlexW2935628582WikidataQ128126077 ScholiaQ128126077MaRDI QIDQ5034189

Meena Badade, T. V. Ramanathan

Publication date: 24 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2019.1597838

zbMATH Keywords

technical efficiencybinary type output dataprobabilistic frontier regression models

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Cites Work

• Unnamed Item
• A gamma-distributed stochastic frontier model
• Asymptotic behavior of the Newton-Boussinesq equation in a two-dimensional channel
• Likelihood functions for generalized stochastic frontier estimation
• Formulation and estimation of stochastic frontier production function models
• Bias free measurement of technical efficiency
• Bayesian Analysis of the Two-Parameter Gamma Distribution
• Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error
• A copula regression model for estimating firm efficiency in the insurance industry
• Comparison of Bayesian models for production efficiency
• A stochastic frontier approach to survival analysis
• Ordinal principal component analysis for a common ranking of stochastic frontiers
• Distribution of cost inefficiency in stochastic frontier approach: evidence from Spanish banking
• Energy performance evaluation of OECD countries using Bayesian stochastic frontier analysis and Bayesian network classifiers

This page was built for publication: Probabilistic frontier regression models for binary type output data