Excess zeros and overdispersion are common phenomena that limit the use of traditional Poisson regression models for modeling count data. Both excess zeros and overdispersion caused by unobserved heterogeneity are accounted for by the proposed zero-inflated Poisson (ZIP) regression mixture...

Based on market basket data, multicategory purchase incidence models analyze demand interdependencies between product categories. We propose a finite mixture multivariate logit model to derive segment-specific intercategory effects of market basket purchase. Under the assumption that only a...

This paper addresses the issue of unobserved heterogeneity in film characteristics influence on box-office. We argue that the analysis of pooled samples, most common among researchers, does not shed light on underlying segmentations and leads to significantly different estimates obtained by...

This paper focuses on analyzing data collected in situations where investigators use multiple discrete indicators as surrogates, for example, a set of questionnaires. A very flexible latent class model is used for analysis. We propose a Bayesian framework to perform the joint estimation of the...

This paper proposes a finite mixture model (FMM) to model the behavioral transition of calorie consumption with an assumption that nutrition consumption is a mixture of two different behavioral stages: a poor stage and an affluent stage. Based on 387 calorie-income elasticities collected from 90...

In this paper we analyze asymmetric information in the (private) disability insurance, which has not been analyzed before in the literature, but covers one of the most important risks faced by individuals in modern society, namely the loss of human capital. We show that there is asymmetric...

The paper proposes a combination of finite mixture models and matching estimators to account for heterogeneous and nonlinear effects of the coinsurance rate on healthcare expenditure. We use loglinear model and generalized linear models with different distribution families, and measure the...

A constructive proof of identification of multilinear decompositions of multiway arrays is presented. It can be applied to show identification in a variety of multivariate latent structures. Examples are finite-mixture models and hidden Markov models. The key step to show identification is the...