圣人 发表于 2025-3-23 10:52:29

Daniel B. Diner,Derek H. FenderThis chapter introduces the computational tools and methods that we use for sampling from the posterior distribution. Since all numerical computations, and Bayesian ones are no exception, may end in errors, we also provide a few tips to check that the numerical computation is sampling from the posterior distribution.

floodgate 发表于 2025-3-23 16:31:42

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词汇表 发表于 2025-3-23 19:23:46

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mitral-valve 发表于 2025-3-24 01:01:17

A Bit of Theory,This short chapter introduces the basics of probability theory in an intuitive fashion using simple examples. It also illustrates, again with examples, how to propagate errors and the difference between marginal and profile likelihoods.

Vulnerable 发表于 2025-3-24 06:26:34

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注入 发表于 2025-3-24 07:20:50

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MITE 发表于 2025-3-24 14:21:28

https://doi.org/10.1007/978-3-319-15287-5Bayesian astrostatistics; Bayesian methods for astronomy; Fitting regression models in physical scienc

SSRIS 发表于 2025-3-24 16:12:09

978-3-319-36783-5Springer Nature Switzerland AG 2015

RAFF 发表于 2025-3-24 19:06:19

Evolving from Earthlings into Martians?ptions). We illustrate this concept with examples where the prior plays greatly different roles, from major to negligible. We also provide some advice on how to look for information useful for sculpting the prior.

分开如此和谐 发表于 2025-3-24 23:56:21

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查看完整版本: Titlebook: Bayesian Methods for the Physical Sciences; Learning from Exampl Stefano Andreon,Brian Weaver Book 2015 Springer Nature Switzerland AG 2015