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Titlebook: Bayesian Statistical Modeling with Stan, R, and Python; Kentaro Matsuura Book 2022 Springer Nature Singapore Pte Ltd. 2022 Stan.Bayesian M

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21#
發(fā)表于 2025-3-25 07:24:10 | 只看該作者
Human Humoral Immunity in SCID MiceWe will discuss several points that can potentially be problematic in extending regression analysis, and how to deal with these issues.
22#
發(fā)表于 2025-3-25 10:40:29 | 只看該作者
23#
發(fā)表于 2025-3-25 12:57:49 | 只看該作者
24#
發(fā)表于 2025-3-25 19:24:11 | 只看該作者
Overview of StanWe will introduce probabilistic programming languages and Stan. We will explain the basic grammar of Stan, with the focuses on block structures, probabilistic generation, and for loop statement. We also give suggestions on the coding styles.
25#
發(fā)表于 2025-3-25 22:34:55 | 只看該作者
26#
發(fā)表于 2025-3-26 02:14:40 | 只看該作者
27#
發(fā)表于 2025-3-26 07:03:59 | 只看該作者
Introduction of Probability DistributionsThis chapter introduces several probability distributions that are commonly used in statistical modeling.?We explain the basic properties of these fundamental distributions, and further provide some examples to explain how to use them in practice, and other information that should be taken into account when building a model with them.
28#
發(fā)表于 2025-3-26 11:50:38 | 只看該作者
Issues of RegressionWe will discuss several points that can potentially be problematic in extending regression analysis, and how to deal with these issues.
29#
發(fā)表于 2025-3-26 14:10:27 | 只看該作者
Other Advanced TopicsWe will introduce some advanced topics that have not been mentioned in the previous chapters.
30#
發(fā)表于 2025-3-26 17:48:27 | 只看該作者
Book 2022 advanced topics for real-world data: longitudinal data analysis, state space models, spatial data analysis, Gaussian processes, Bayesian optimization, dimensionality reduction, model selection, and information criteria, demonstrating that Stan can solve any one of these problems in as little as 30
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