A0200
Title: Shrinkage estimators for beta regression models
Authors: Luis Alberto Firinguetti Limone - Universidad del Bio-Bio (Chile) [presenting]
Luis Gomez - Universidad del Bio-Bio (Chile)
Abstract: The beta regression model is a useful framework for studying response variables which are rates or proportions, that is to say, response variables which are continuous and restricted to the interval $(0,1)$. As with any other regression model, parameter estimates may be affected by collinearity, or even perfect collinearity, among the explanatory variables. To handle these situations, shrinkage estimators are proposed. In particular, we develop Ridge Regression and LASSO estimators from a penalized likelihood perspective with a logit link function. The properties of the resulting estimators are evaluated through simulation experiments.
