000 02651nam a2200325| 4500
001 83997
005 20220104105100.0
010 _a978-3-319-19518-6
_dcompra
090 _a83997
100 _a20190128d2015 k||y0pory50 ba
101 _aeng
102 _aCH
200 _aNonparametric bayesian inference in biostatistics
_bDocumento eletrn̤ico
_f
210 _aCham
_cSpringer International Publishing
_d2015
215 _aXVII, 448 p.
_cil.
225 _aFrontiers in Probability and the Statistical Sciences
300 _aColocaȯ̂: Online
303 _aAs 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. Riten Mitra is Assistant Professor in the Department of Bioinformatics and Biostatistics at University of Louisville. His research interests include Bayesian graphical models and nonparametric Bayesian methods with a special emphasis on applications in genomics and bioinformatics. Peter Mueller is Professor in the Department of Mathematics and the Department of Statistics & Data Science at the University of Texas at Austin. He has published widely on nonparametric Bayesian statistics, with an emphasis on applications in biostatistics and bioinformatics.
410 _x2624-9987
606 _93627
_aEstats̕tica
606 _935379
_aBioestats̕tica
680 _aQA276
702 _933450
_aMitra
_bRiten
_4340
702 _933451
_a
_bPeter
_4340
801 _gRPC
_aPT
856 _uhttps://doi.org/10.1007/978-3-319-19518-6
942 _2lcc
_cF
_n0