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【预订】Bayesian Nonparametrics for Causal Inference and Missing 国外库房发货，通常付款后3-5周到货！
Product Details 基本信息 ISBN-13 书号 9780367341008 Author 作者 Daniels Format 版本 精装 Pages Number 页数 262页 Publisher 出版社 CRC Press Publication Date 出版日期 2023-08-23 Product Dimensions 商品尺寸 234 x 156 mm (6.14 x 9.21 Language 语种 其它（含多语） Book Contents 内容简介 Bayesian Nonparametrics for Causal Inference and Missing Data provides an overview of flexible Bayesian nonparametric (BNP) methods for modeling joint or conditional distributions and functional relationships, and their interplay with causal inference and missing data. This book emphasizes the importance of making untestable assumptions to identify estimands of interest, such as missing at random assumption for missing data and unconfoundedness for causal inference in observational studies. Unlike parametric methods, the BNP approach can account for possible violations of assumptions and minimize concerns about m
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Product Details 基本信息 ISBN-13 书号 9781441930446 Author 作者 Ghosh Format 版本 平装-胶订 Pages Number 页数 308页 Publication Date 出版日期 2010-12-01 Language 语种 英语 Book Contents 内容简介 Bayesian nonparametrics has grown tremendously in the last three decades, especially in the last few years. This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. While the book is of special interest to Bayesians, it will also appeal to statisticians in general because Bayesian nonparametrics offers a whole continuous spectrum of robust alternatives to purely parametric and purely nonparametric methods of classical statistics. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian nonparametrics. Though the emphasis of the book is on nonparametrics, there is a substantial chapter on asymptotics of classical Bayesia
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英文原版 Bayesian Nonparametrics 贝叶斯非参数方法 剑桥统计与概率数学系列 精装 英文版 进口英
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