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Více informací o knize Nonparametric Bayesian Inference in Biostatistics

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Anotace knihy

As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters cover: clinical trials, spatial inference, proteomics, genomics, clustering, survival analysis and ROC curve.§§

Parametry knihy

Zařazení knihy Knihy v angličtině Mathematics & science Biology, life sciences Life sciences: general issues

• Plný název: Nonparametric Bayesian Inference in Biostatistics
• Autor: Peter Mueller, Riten Mitra
• Jazyk: Angličtina
• Vazba: Pevná
• Počet stran: 448
• EAN: 9783319195179
• ISBN: 3319195174
• ID: 09285199
• Nakladatelství: Springer International Publishing AG
• Hmotnost: 916 g
• Rozměry: 163 × 285 × 29 mm
• Datum vydání: 28. July 2015

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