A computational Bayesian approach to Poisson regression models-a simulation study

Poisson regression is a kind of regression analysis that describes count data using a generalized linear model. A frequentist method for these models is to apply reweighted least-squares iteratively to determine the maximum likelihood estimators (MLE). In this study, we compare the effectiveness of...

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Bibliographische Detailangaben

Hauptverfasser:	Al-Sharifi, Sanaa Noor Mohammed, Al Baldawi, Tasnim H. K.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithms Bayesian analysis Computer simulation Estimation Generalized linear models Markov chains Maximum likelihood estimators Mean Performance evaluation Poisson density functions Random walk Regression analysis Regression models Statistical models
Online-Zugang:	Volltext
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