ABSTRACT
The paper provides a Bayesian analysis for the zero-inflated regression models based on the generalized power series distribution. The approach is based on Markov chain Monte Carlo methods. The residual analysis is discussed and case-deletion influence diagnostics are developed for the joint posterior distribution, based on the ψ-divergence, which includes several divergence measures such as the Kullback–Leibler, J-distance, L1 norm, and χ2-square in zero-inflated general power series models. The methodology is reflected in a data set collected by wildlife biologists in a state park in California.
Mathematics Subject Classification: