Monte Carlo algorithsm for Bayesian inference
<p>This thesis addresses several issues appearing in Bayesian statistics. Firstly, computations for approximating Bayesian posteriors are often performed using Markov chain Monte Carlo (MCMC) methods. However, standard MCMC algorithms tend to perform poorly when the posterior distribution has...
Κύριος συγγραφέας: | Pompe, E |
---|---|
Άλλοι συγγραφείς: | Holmes, C |
Μορφή: | Thesis |
Γλώσσα: | English |
Έκδοση: |
2021
|
Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
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Markov chain Monte Carlo : stochastic simulation for Bayesian inference /
ανά: 360681 Gamerman, Dani, κ.ά.
Έκδοση: (2006) -
Photometric Calibrations of M-dwarf Metallicity with Markov Chain Monte Carlo and Bayesian Inference
ανά: C. Duque-Arribas, κ.ά.
Έκδοση: (2023-01-01) -
Measuring diachronic sense change: new models and Monte Carlo methods for Bayesian inference
ανά: Zafar, S, κ.ά.
Έκδοση: (2022) -
Bayesian statistics and Monte Carlo methods
ανά: Koch K. R.
Έκδοση: (2018-03-01) -
Approximating multivariate posterior distribution functions from Monte Carlo samples for sequential Bayesian inference.
ανά: Bram Thijssen, κ.ά.
Έκδοση: (2020-01-01)