Bayesian nonparametric data analysis [Documento eletrónico] / Peter Müller ... [et al.]
Language: eng.Country: Switzerland, Swiss Confederation.Publication: Cham : Springer International Publishing, 2015Description: XIV, 193 p. : il.ISBN: 978-3-319-18968-0.Series: Springer Series in StatisticsSubject - Topical Name: Estatística matemática | Estatística Online Resources:Click here to access onlineItem type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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E-Books | Biblioteca NOVA FCT Online | Não Ficção | QA276.SPR FCT 96578 (Browse shelf(Opens below)) | 1 | Available |
Colocação: Online
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 on-line software pages.
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