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Full-Text Articles in Statistical Models
Finite Mixtures Of Mean-Parameterized Conway-Maxwell-Poisson Models, Dongying Zhan
Finite Mixtures Of Mean-Parameterized Conway-Maxwell-Poisson Models, Dongying Zhan
Theses and Dissertations--Statistics
For modeling count data, the Conway-Maxwell-Poisson (CMP) distribution is a popular generalization of the Poisson distribution due to its ability to characterize data over- or under-dispersion. While the classic parameterization of the CMP has been well-studied, its main drawback is that it is does not directly model the mean of the counts. This is mitigated by using a mean-parameterized version of the CMP distribution. In this work, we are concerned with the setting where count data may be comprised of subpopulations, each possibly having varying degrees of data dispersion. Thus, we propose a finite mixture of mean-parameterized CMP distributions. An …
A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele
A Flexible Zero-Inflated Poisson Regression Model, Eric S. Roemmele
Theses and Dissertations--Statistics
A practical problem often encountered with observed count data is the presence of excess zeros. Zero-inflation in count data can easily be handled by zero-inflated models, which is a two-component mixture of a point mass at zero and a discrete distribution for the count data. In the presence of predictors, zero-inflated Poisson (ZIP) regression models are, perhaps, the most commonly used. However, the fully parametric ZIP regression model could sometimes be restrictive, especially with respect to the mixing proportions. Taking inspiration from some of the recent literature on semiparametric mixtures of regressions models for flexible mixture modeling, we propose a …