R package betareg: Beta Regression. Beta regression for modeling beta-distributed dependent variables, e.g., rates and proportions. In addition to maximum likelihood regression (for both mean and precision of a beta-distributed response), bias-corrected and bias-reduced estimation as well as finite mixture models and recursive partitioning for beta regressions are provided.
Keywords for this software
References in zbMATH (referenced in 11 articles )
Showing results 1 to 11 of 11.
- Cepeda-Cuervo, Edilberto; Jaimes, Daniel; Marín, Margarita; Rojas, Javier: Bayesian beta regression with Bayesianbetareg R-package (2016)
- Iannario, Maria; Piccolo, Domenico: A comprehensive framework of regression models for ordinal data (2016)
- Irvine, Kathryn M.; Rodhouse, T.J.; Keren, Ilai N.: Extending ordinal regression with a latent zero-augmented beta distribution (2016)
- Jodrá, P.; Jiménez-Gamero, M.D.: A note on the log-Lindley distribution (2016)
- Shou, Yiyun; Smithson, Michael: Evaluating predictors of dispersion: a comparison of dominance analysis and Bayesian model averaging (2015)
- Espinheira, Patrícia L.; Ferrari, Silvia L.P.; Cribari-Neto, Francisco: Bootstrap prediction intervals in beta regressions (2014)
- Guolo, Annamaria; Varin, Cristiano: Beta regression for time series analysis of bounded data, with application to Canada $\mathrmGoogle^\circledR$ Flu Trends (2014)
- Chien, Li-Chu: Multiple deletion diagnostics in beta regression models (2013)
- Mitnik, Pablo A.; Baek, Sunyoung: The Kumaraswamy distribution: median-dispersion re-parameterizations for regression modeling and simulation-based estimation (2013)
- Kosmidis, Ioannis; Firth, David: A generic algorithm for reducing bias in parametric estimation (2010)
- Zeileis, Achim: Implementing a class of structural change tests: An econometric computing approach (2006)