國立虎尾科技大學 |

Nonparametric Bayesian Inference in Biostatistics

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Nonparametric Bayesian Inference in Biostatistics/ edited by Riten Mitra, Peter Müller.
其他作者:	Mitra, Riten.
面頁冊數:	XVII, 448 p. 96 illus., 47 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Statistics . -
電子資源:	https://doi.org/10.1007/978-3-319-19518-6
ISBN:	9783319195186

Nonparametric Bayesian Inference in Biostatistics
Nonparametric Bayesian Inference in Biostatistics[electronic resource] /edited by Riten Mitra, Peter Müller. - 1st ed. 2015. - XVII, 448 p. 96 illus., 47 illus. in color.online resource. - Frontiers in Probability and the Statistical Sciences,2624-9987. - Frontiers in Probability and the Statistical Sciences,.

Part I Introduction -- Bayesian Nonparametric Models -- Bayesian Nonparametric Biostatistics -- Part II Genomics and Proteomics -- Bayesian Shape Clustering -- Estimating Latent Cell Subpopulations with Bayesian Feature Allocation Models -- Species Sampling Priors for Modeling Dependence: An Application to the Detection of Chromosomal Aberrations -- Modeling the Association Between Clusters of SNPs and Disease Responses -- Bayesian Inference on Population Structure: from Parametric to Nonparametric Modeling -- Bayesian Approaches for Large Biological Networks -- Nonparametric Variable Selection, Clustering and Prediction for Large Biological Datasets -- Part III Survival Analysis -- Markov Processes in Survival Analysis -- Bayesian Spatial Survival Models -- Fully Nonparametric Regression Modelling of Misclassified Censored Time-to-Event Data -- Part IV Random Functions and Response Surfaces -- Neuronal Spike Train Analysis Using Gaussian Process Models -- Bayesian Analysis of Curves Shape Variation through Registration and Regression -- Biomarker-Driven Adaptive Design -- Bayesian Nonparametric Approaches for ROC Curve Inference -- Part V Spatial Data -- Spatial Bayesian Nonparametric Methods -- Spatial Species Sampling and Product Partition Models -- Spatial Boundary Detection for Areal Counts -- A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs -- Bayesian Nonparametrics for Missing Data in Longitudinal Clinical Trials.

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. 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.

ISBN: 9783319195186

Standard No.: 10.1007/978-3-319-19518-6doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Nonparametric Bayesian Inference in Biostatistics
LDR:04650nam a22004215i 4500 001 970215
003 DE-He213
005 20200630031713.0
007 cr nn 008mamaa
008 201211s2015 gw | s |||| 0|eng d
020 $a 9783319195186 $9 978-3-319-19518-6
024 7 $a 10.1007/978-3-319-19518-6 $2 doi
035 $a 978-3-319-19518-6
050 4 $a QA276-280
072 7 $a PBT $2 bicssc
072 7 $a MED090000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a MBNS $2 thema
082 0 4 $a 519.5 $2 23
245 1 0 $a Nonparametric Bayesian Inference in Biostatistics $h [electronic resource] / $c edited by Riten Mitra, Peter Müller.
250 $a 1st ed. 2015.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a XVII, 448 p. 96 illus., 47 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Frontiers in Probability and the Statistical Sciences, $x 2624-9987
505 0 $a Part I Introduction -- Bayesian Nonparametric Models -- Bayesian Nonparametric Biostatistics -- Part II Genomics and Proteomics -- Bayesian Shape Clustering -- Estimating Latent Cell Subpopulations with Bayesian Feature Allocation Models -- Species Sampling Priors for Modeling Dependence: An Application to the Detection of Chromosomal Aberrations -- Modeling the Association Between Clusters of SNPs and Disease Responses -- Bayesian Inference on Population Structure: from Parametric to Nonparametric Modeling -- Bayesian Approaches for Large Biological Networks -- Nonparametric Variable Selection, Clustering and Prediction for Large Biological Datasets -- Part III Survival Analysis -- Markov Processes in Survival Analysis -- Bayesian Spatial Survival Models -- Fully Nonparametric Regression Modelling of Misclassified Censored Time-to-Event Data -- Part IV Random Functions and Response Surfaces -- Neuronal Spike Train Analysis Using Gaussian Process Models -- Bayesian Analysis of Curves Shape Variation through Registration and Regression -- Biomarker-Driven Adaptive Design -- Bayesian Nonparametric Approaches for ROC Curve Inference -- Part V Spatial Data -- Spatial Bayesian Nonparametric Methods -- Spatial Species Sampling and Product Partition Models -- Spatial Boundary Detection for Areal Counts -- A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs -- Bayesian Nonparametrics for Missing Data in Longitudinal Clinical Trials.
520 $a 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. 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.
650 0 $a Statistics . $3 1253516
650 0 $a Biostatistics. $3 783654
650 1 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 670172
650 2 4 $a Statistical Theory and Methods. $3 671396
700 1 $a Mitra, Riten. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1067402
700 1 $a Müller, Peter. $e author. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 1257225
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319195179
776 0 8 $i Printed edition: $z 9783319195193
776 0 8 $i Printed edition: $z 9783319368177
830 0 $a Frontiers in Probability and the Statistical Sciences, $x 2624-9987 $3 1264369
856 4 0 $u https://doi.org/10.1007/978-3-319-19518-6
912 $a ZDB-2-SMA
912 $a ZDB-2-SXMS
950 $a Mathematics and Statistics (SpringerNature-11649)
950 $a Mathematics and Statistics (R0) (SpringerNature-43713)