Bayesian Compendium
Marcel van Oijen ()
in Springer Books from Springer
Date: 2024
Edition: Second Edition 2024
ISBN: 978-3-031-66085-6
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Chapters in this book:
- Ch Chapter 1 Science and Uncertainty
- Marcel van Oijen
- Ch Chapter 10 After the Calibration: Interpretation, Reporting, Visualisation
- Marcel van Oijen
- Ch Chapter 11 Model Ensembles: BMC and BMA
- Marcel van Oijen
- Ch Chapter 12 Discrepancy
- Marcel van Oijen
- Ch Chapter 13 Approximations to Bayes
- Marcel van Oijen
- Ch Chapter 14 Thirteen Ways to Fit a Straight Line
- Marcel van Oijen
- Ch Chapter 15 Gaussian Processes and Model Emulation
- Marcel van Oijen
- Ch Chapter 16 Graphical Modelling
- Marcel van Oijen
- Ch Chapter 17 Bayesian Hierarchical Modelling
- Marcel van Oijen
- Ch Chapter 18 Probabilistic Risk Analysis
- Marcel van Oijen
- Ch Chapter 19 Bayesian Decision Theory
- Marcel van Oijen
- Ch Chapter 2 Bayesian Inference
- Marcel van Oijen
- Ch Chapter 20 Linear Modelling: LM, GLM, GAM and Mixed Models
- Marcel van Oijen
- Ch Chapter 21 Machine Learning
- Marcel van Oijen
- Ch Chapter 22 Time Series and Data Assimilation
- Marcel van Oijen
- Ch Chapter 23 Spatial Modelling and Scaling Error
- Marcel van Oijen
- Ch Chapter 24 Spatio-Temporal Modelling and Adaptive Sampling
- Marcel van Oijen
- Ch Chapter 25 What Next?
- Marcel van Oijen
- Ch Chapter 3 Assigning a Prior Distribution
- Marcel van Oijen
- Ch Chapter 4 Assigning a Likelihood Function
- Marcel van Oijen
- Ch Chapter 5 Deriving the Posterior Distribution
- Marcel van Oijen
- Ch Chapter 6 Markov Chain Monte Carlo Sampling (MCMC)
- Marcel van Oijen
- Ch Chapter 7 Sampling from the Posterior Distribution by MCMC
- Marcel van Oijen
- Ch Chapter 8 MCMC and Multivariate Models
- Marcel van Oijen
- Ch Chapter 9 Bayesian Calibration and MCMC: Frequently Asked Questions
- Marcel van Oijen
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprbok:978-3-031-66085-6
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DOI: 10.1007/978-3-031-66085-6
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