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Titlebook: Bayesian Nonparametric Data Analysis; Peter Müller,Fernando Andres Quintana,Tim Hanson Book 2015 Springer International Publishing Switzer

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發(fā)表于 2025-3-21 16:23:20 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Bayesian Nonparametric Data Analysis
影響因子2023Peter Müller,Fernando Andres Quintana,Tim Hanson
視頻videohttp://file.papertrans.cn/182/181870/181870.mp4
發(fā)行地址This is the first text to introduce nonparametric Bayesian inference from a data analysis perspective.Includes a large number of examples to illustrate the application of nonparametric Bayesian models
學(xué)科分類Springer Series in Statistics
圖書封面Titlebook: Bayesian Nonparametric Data Analysis;  Peter Müller,Fernando Andres Quintana,Tim Hanson Book 2015 Springer International Publishing Switzer
影響因子This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. .The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages..
Pindex Book 2015
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發(fā)表于 2025-3-21 20:30:04 | 只看該作者
Human Freedom and the Logic of Eviloral data, model validation and causal inference. These themes are introduced to show by example the nature of the many application areas of nonparametric Bayesian inference that we did not include in earlier chapter.
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Domènec Melé,César González Cantóncomes particularly interesting in the presence of covariates, when non- and semi-parametric Bayesian models can generalize the link function in a generalized linear model setup, the regression on covariates or both. An important application arises in inference for diagnostic screening and related in
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發(fā)表于 2025-3-22 20:13:56 | 只看該作者
Feelings, Emotions, and Aesthetic Experienceical applications, it is natural to focus on inference for detailed features of the survival function rather than only summaries like mean and variance. We extensively discuss semi- and nonparametric Bayesian methods for survival regression. Inference for such data has been traditionally dominated b
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發(fā)表于 2025-3-22 22:47:34 | 只看該作者
On the Use of Scientific Argumentsre the main inference targets for many recently published applications of nonparametric Bayesian discrete mixture models. In this chapter we systematically consider the use of nonparametric Bayesian priors for inference on such random partitions. Many scientific inference problems are formalized as
9#
發(fā)表于 2025-3-23 02:57:06 | 只看該作者
Human Freedom and the Logic of Eviloral data, model validation and causal inference. These themes are introduced to show by example the nature of the many application areas of nonparametric Bayesian inference that we did not include in earlier chapter.
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發(fā)表于 2025-3-23 07:18:10 | 只看該作者
Other Inference Problems and Conclusion,oral data, model validation and causal inference. These themes are introduced to show by example the nature of the many application areas of nonparametric Bayesian inference that we did not include in earlier chapter.
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