Bayesian Approach for GLM

M. Ataharul Islam () and Soma Chowdhury Biswas ()
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M. Ataharul Islam: University of Dhaka, ISRT
Soma Chowdhury Biswas: University of Chittagong, Department of Statistics

Chapter Chapter 11 in Generalized Linear Models and Extensions, 2025, pp 199-211 from Springer

Abstract: Abstract The Bayesian approach for GLM is discussed taking into account probability statements about parameters for any given set of data. In this chapter the assumptions are made on the model parameters in the form of prior distribution. In Bayesian generalized linear models’ framework, we have considered models for binary, multinomial, count data multivariate responses. This chapter includes a section on big data Bayesian GLM to make the users familiar with the increasingly useful Bayesian approaches to analyse the problems emerging from big data analytics.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-96-4726-2_11

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DOI: 10.1007/978-981-96-4726-2_11

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