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- 7.000.000 titres dans notre catalogue
- Payer en toute sécurité
- Toujours un magasin près de chez vous
Nonparametric Bayesian Inference in Biostatistics
105,45 €
+ 210 points
Description
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.
Spécifications
Parties prenantes
- Editeur:
Contenu
- Nombre de pages :
- 448
- Langue:
- Anglais
- Collection :
Caractéristiques
- EAN:
- 9783319368177
- Date de parution :
- 15-10-16
- Format:
- Livre broché
- Format numérique:
- Trade paperback (VS)
- Dimensions :
- 155 mm x 235 mm
- Poids :
- 7873 g
