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Poisson generalized Lindley process and its properties
In spite of the practical usefulness of the nonhomogeneous Poisson process, it still has some restrictions. To overcome these restrictions, the...
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A Flexible Generalized Poisson Likelihood for Spatial Counts Constructed by Renewal Theory, Motivated by Groundwater Quality Assessment
In recent years, the availability of spatial count data has massively increased. Due to the ubiquity of over- or under-dispersion in count data, we...
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Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression
In this paper, we present a novel family of multivariate mixed Poisson-Generalized Inverse Gaussian INAR(1), MMPGIG-INAR(1), regression models for...
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Generalized log-gamma additive partial linear models with P-spline smoothing
In this paper additive partial linear models with generalized log-gamma errors and P-spline smoothing are proposed for uncensored data. This class...
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On Properties of the Phase-type Mixed Poisson Process and its Applications to Reliability Shock Modeling
Although Poisson processes are widely used in various applications for modeling of recurrent point events, there exist obvious limitations. Several...
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Quantile-based control charts for poisson and gamma distributed data
In terms of statistical process control (SPC), the probability distributions of the quality characteristics are critical in detecting changes in the...
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Doubly-Inflated Poisson INGARCH Models for Count Time Series
Researchers usually model count time series data assuming the responses follow the Poisson distribution. The Poisson distribution is often a suitable...
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A generalized Hosmer–Lemeshow goodness-of-fit test for a family of generalized linear models
Generalized linear models (GLMs) are very widely used, but formal goodness-of-fit (GOF) tests for the overall fit of the model seem to be in wide use...
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A New Regression Model for Over-Dispersed Count Responses Based on Poisson and Geometric Convolution
This article presents an alternative generalized linear regression model specifically designed for count responses that exhibit over-dispersion. The...
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Fiducial-Based Statistical Intervals for Zero-Inflated Gamma Data
In practice, it is not uncommon to observe count data that possess excessive zeros (i.e., zero inflation) relative to the assumed discrete...
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On Computing the Multivariate Poisson Probability Distribution
Within the theory of non-negative integer valued multivariate infinitely divisible distributions, the multivariate Poisson distribution plays a key...
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On Estimation of Stress-Strength Reliability with Zero-Inflated Poisson Distribution
Many real-world phenomena generate count data with inflated number of zeroes. To model such datasets, the zero-inflated Poisson model has been used...
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Flexible Modeling of Hurdle Conway–Maxwell–Poisson Distributions with Application to Mining Injuries
The Poisson regression is the most popular class of models for count data, but with excessive zeros and unequal dispersion, the ordinary Poisson may...
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Taylor’s power law and reduced-rank vector generalized linear models
Taylor’s power law (TPL) from empirical ecological theory has had many explanations proposed for its widespread observation in data. We show that the...
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Generalized mixed spatiotemporal modeling with a continuous response and random effect via factor analysis
This work focuses on Generalized Linear Mixed Models that incorporate spatiotemporal random effects structured via Factor Model (FM) with nonlinear...
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On the Time-Dependent Delta-Shock Model Governed by the Generalized PóLya Process
One of the widely discussed in the literature and relevant in practice shock models is the delta-shock model that is described by the constant time...
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The Pareto–Poisson Distribution: Characteristics, Estimations and Engineering Applications
A new three-parameter lifetime distribution based on compounding Pareto and Poisson distributions is introduced and discussed. Various statistical...
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Bootstrap** generalized linear models to accommodate overdispersed count data
When modelling counts or rates using Poisson regression, it is common to find overdispersion in data. Overdispersed count data is prevalent in a...
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Modelling and diagnostic tests for Poisson and negative-binomial count time series
When modelling unbounded counts, their marginals are often assumed to follow either Poisson (Poi) or negative binomial (NB) distributions. To test...
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Equivariance and Invariance for Optimal Designs in Generalized Linear Models Exemplified by a Class of Gamma Models
The main intention of the present work is to outline the concept of equivariance and invariance in the design of experiments for generalized linear...
