Bayesian Binary reciprocal LASSO quantile regression (with practical application)

Abstract

In this research paper, quantitative regression was studied because of its great importance in application in various fields of science. There are many researchers who have dealt with the topic of quantile regression with binary data, that is, when the response variable (y) takes only two values, either (0) or (1), using classical methods as well as Bayesian methods. In this study, the researcher is trying to build a model for analyzing binary data using the Quintile Regression method. The Bayesian method was adopted, which is one of the methods that has gained wide resonance recently because of its accuracy, especially in small samples. In addition, the researcher restricted the study by using inverse penalty functions to select explanatory variables that actually have an effect on the dependent variable, and to exclude ineffective variables using variable selection methods..