Modeling clustered count data with discrete weibull regression model-Reference-Cited by-同舟云学术

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Modeling clustered count data with discrete weibull regression model

Published:2022-07-31 Issue:4 Volume:29 Page:413-420
ISSN:2287-7843
Container-title:Communications for Statistical Applications and Methods
language:en
Short-container-title:Communications for Statistical Applications and Methods

Author:

Yoo Hanna¹

Affiliation:

1. Department of Big Data, Busan University of Foreign Studies, Korea

Publisher

Communications for Statistical Applications and Methods

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Finance,Modeling and Simulation,Statistics and Probability

Link

http://pdf.medrang.co.kr/CSAM/2022/029/CSAM029-04-413.pdf

Reference14 articles.

1. Alan B and Nial F (2021). Bayesian inference, model selection and likelihood estimation using fast rejection sampling: The Conway-Maxwell-Poisson distribution. Bayesian Analysis, 16, 905-931.

2. Albert J (1992). A Bayesian analysis of a Poisson random effects model for home run hitters. The American Statistician, 46, 246-253.

3. A bivariate count model with discrete Weibull margins

4. Dunlop D (1994). Regression for longitudinal data: A bridge from least squares regression. The American Statistician, 48, 299-303.

5. Zero-Inflated Poisson and Binomial Regression with Random Effects: A Case Study

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