Retrieval
发表于 2025-3-25 07:13:24
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中世纪
发表于 2025-3-25 11:06:13
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etiquette
发表于 2025-3-25 15:36:52
Introduction to Bayesian Computation,r functional form, such as a member of an exponential family, and a conjugate prior is chosen for the parameter, then the posterior distribution often is expressible in terms of familiar probability distributions.
FRAX-tool
发表于 2025-3-25 18:07:38
Hierarchical Modeling,odeling. Then we consider the simultaneous estimation of the true mortality rates from heart transplants for a large number of hospitals. Some of the individual estimated mortality rates are based on limited data, and it may be desirable to combine the individual rates in some way to obtain more accurate estimates.
Banquet
发表于 2025-3-25 21:36:35
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exquisite
发表于 2025-3-26 01:37:17
Bayesian Computation with R978-0-387-92298-0Series ISSN 2197-5736 Series E-ISSN 2197-5744
Arteriography
发表于 2025-3-26 05:33:56
A Brief Review of Immigration from Asia,sian inference for a variance for a normal population and inference for a Poisson mean when informative prior information is available. For both problems, summarization of the posterior distribution is facilitated by the use of R functions to compute and simulate distributions from the exponential family.
十字架
发表于 2025-3-26 12:17:26
https://doi.org/10.1007/978-981-99-4997-7r functional form, such as a member of an exponential family, and a conjugate prior is chosen for the parameter, then the posterior distribution often is expressible in terms of familiar probability distributions.
辞职
发表于 2025-3-26 16:12:13
https://doi.org/10.1007/978-981-99-4997-7odeling. Then we consider the simultaneous estimation of the true mortality rates from heart transplants for a large number of hospitals. Some of the individual estimated mortality rates are based on limited data, and it may be desirable to combine the individual rates in some way to obtain more accurate estimates.
Lymphocyte
发表于 2025-3-26 17:21:06
https://doi.org/10.1007/978-981-99-4997-7ppose that we partition the parameter vector of interest into . components ., where . may consist of a vector of parameters. The MCMC algorithm is implemented by sampling in turn from the . conditional posterior distributions.