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[ subject:"Bayesian statistical decision theory" ]
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Bayesian nonparametric methods for missing data and causal inference /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Bayesian nonparametric methods for missing data and causal inference /Michael J. Daniels, Antonio Linero, and Jason Roy.
作者:
Daniels, M. J.
其他作者:
Linero, Antonio,
面頁冊數:
xiv, 248pages :illustrations ;25cm.
標題:
Nonparametric statistics.
ISBN:
9780429324222$q(ebook)
Bayesian nonparametric methods for missing data and causal inference /
Daniels, M. J.
Bayesian nonparametric methods for missing data and causal inference /
Michael J. Daniels, Antonio Linero, and Jason Roy. - First edition. - xiv, 248pages :illustrations ;25cm. - Chapman & Hall/CRC monographs on statistics and applied probability.
Includes bibliographical references and index.
"Bayesian nonparametric (BNP) methods can be used to flexibly model joint or conditional distributions, as well as functional relationships. These methods, along with causal and/or missingness assumptions, can be used with the g-formula to infer causal effects"--
ISBN: 9780429324222$q(ebook)
LCCN: 2023007544Subjects--Topical Terms:
182700
Nonparametric statistics.
LC Class. No.: QA278.8
Dewey Class. No.: 519.5/4
Bayesian nonparametric methods for missing data and causal inference /
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