Count data with excess zeros arises in many contexts. Here our concern is to develop a Bayesian analysis for the zero-inflated generalized Poisson (ZIGP) regression model to address this problem. This model provides a useful generalization of zero-inflated Poisson model since the generalized...

Zero-inflated Poisson (ZIP) regression model is a popular approach to the analysis of count data with excess zeros. For correlated count data where the observations are either repeated or clustered outcomes from individual subjects, ZIP mixed regression model may be appropriate. However, ZIP...

For the data from multivariate t distributions, it is very hard to make an influence analysis based on the probability density function since its expression is intractable. In this paper, we present a technique for influence analysis based on the mixture distribution and EM algorithm. In fact,...

Homogeneity of dispersion parameters and zero-inflation parameters is a standard assumption in zero-inflated generalized Poisson regression (ZIGPR) models. However, this assumption may be not appropriate in some situations. This work develops a score test for varying dispersion and/or...

Regression model with skew-normal errors provides useful extension for ordinary normal regression models when the data set under consideration involves asymmetric outcomes. On the other hand, the homogeneity of variances (if they exist) is a standard assumption in skew-normal nonlinear...

Recently Lin & Wei (2003) developed the score test for heteroscedasticity in nonlinear regression models and investigated the power of this test through Monte Carlo simulations. This paper presents an approach for estimating local power of the score test, based on an asymptotic approximation to...