Marginalized mixture models for count data from multiple source populations
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Publication:1690454
DOI10.1186/s40488-017-0057-4OpenAlexW2604482336WikidataQ36356628 ScholiaQ36356628MaRDI QIDQ1690454
John S. Preisser, Habtamu K. Benecha, Kimon Divaris, Brian Neelon
Publication date: 19 January 2018
Published in: Journal of Statistical Distributions and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1186/s40488-017-0057-4
Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Generalized linear models (logistic models) (62J12)
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Cites Work
- Medical applications of finite mixture models
- Marginalized mixture models for count data from multiple source populations
- A mixture likelihood approach for generalized linear models
- Testing overdispersion in the zero-inflated Poisson model
- Finite mixture and Markov switching models.
- Marginal mean models for zero-inflated count data
- A Score Test for Testing a Zero‐Inflated Poisson Regression Model Against Zero‐Inflated Negative Binomial Alternatives
- The zero-inflated negative binomial regression model with correction for misclassification: an example in caries research
- Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
- Mixed Poisson Regression Models with Covariate Dependent Rates
- Random effect models for repeated measures of zero-inflated count data