# Local influence measure of zero inflated generalized poisson mixture regression models

##### *2020-02-22 09:39*

For example, zeroinflated models add a proportion of zeros (usually from a bernoulli process) to the zeros of a Poisson process. Hurdle models are twopart models where zeros and nonzeros are generated by different stochastic processes. Zeroinflated and hurdle models are described in detail by Cameron and Trivedi (1998) and cannot be fit withZeroinflated poisson regression is used to model count data that has an excess of zero counts. Further, theory suggests that the excess zeros are generated by a separate process from the count values and that the excess zeros can be modeled independently. local influence measure of zero inflated generalized poisson mixture regression models

Mar 14, 2013 In this paper, we deal with a class of twocomponent zeroinflated generalized Poisson mixture regression models to fit such data and propose a local influence measure procedure for model comparison and statistical diagnostics.

Aug 07, 2012 The zero inflated Poisson (ZIP) model is one way to allow for overdispersion. This model assumes that the sample is a mixture of two sorts of individuals: one group whose counts are generated by the standard Poisson regression model, and another group (call them the absolute zero group) who have zero probability of a count greater than 0. ZeroInated Generalized Poisson Regression 119 count data with too many zeros. The rest of the paper is organized as follows: In section 2, we describe the domestic violence data. We develop the zeroinated generalized Poisson (ZIGP) regression model in section 3.**local influence measure of zero inflated generalized poisson mixture regression models** In this paper, an extension of zeroinflated Poisson mixed regression models is presented for dealing with multilevel data set, referred as hierarchical mixture zeroinflated Poisson mixed