Pemodelan Regresi Logistik Biner Dengan Pendekatan Bayesian Markov Chain Mont…

ABSTRACT The Poverty Gap Index (PGI) is the average expenditure gap of each poor population towards the poverty line. This study aims to model PGI data using binary logistic regression with a classical approach using the Maximum Likelihood Estimation (MLE) method and a Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. MCMC is a popular method for obtaining information about t…