Diagnostic plots in beta-regression models

Abstract

Two diagnostic plots for selecting explanatory variables are introduced to assess the accuracy of a generalized beta-linear model. The added variable plot is developed to examine the need for adding a new explanatory variable to the model. The constructed variable plot is developed to identify the nonlinearity of the explanatory variable in the model. The two diagnostic procedures are also useful for detecting unusual observations that may affect the regression much. Simulation studies and analysis of two practical examples are conducted to illustrate the performances of the proposed plots.