James Stein Estimator for the Beta Regression Model with Application to Heat-Treating Test and Body Fat Datasets

The beta regression model (BRM) is used when the dependent variable may take continuous values and be bounded in interval (0, 1), such as rates, proportions, percentages fractions. Generally, parameters of BRM are estimated by method maximum likelihood estimation (MLE). However, MLE does not offer accurate reliable estimates explanatory variables correlated. To solve this problem, ridge Liu estimators for were proposed different authors. In current study, James Stein Estimator (JSE) proposed. matrix mean squared error (MSE) scalar MSE properties derived then compared to available estimator, estimator MLE. performance evaluated conducting a simulation experiment analyzing two real-life applications. considered evaluation criterion. findings applications indicate superiority suggested over competitive estimating BRM.