Bayesian models for Astrophysical data
Resources for Bayesian Models for Astrophysical Data - using R, JAGS, Python and Stan - by Hilbe, de Souza and Ishida, 2017, Cambridge University Press
Complete book website: www.BayesianModelsForAstrophysicalData.com
The book can be purchased at Cambridge University Press
Table of Contents
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Chapter 2: Pre-equisites
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Chapter 3: Frequentist vs Bayesian methods
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Chapter 4: Normal linear models
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Chapter 5: GLM part I - continuous and binomial models
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Chapter 6: GLM part II - count models
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Chapter 7: GLM part III - zero-inflated and hurdle models
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Chapter 8: Hierarchical GLMMs
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Chapter 9: Model selection
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Chapter 10: Astronomical applications
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Appendix A: Bayesian Modeling using INLA
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Appendix B: Count Models with Offsets