The Resource Nonparametric Bayesian inference in biostatistics, Riten Mitra, Peter Müller, editors

Nonparametric Bayesian inference in biostatistics, Riten Mitra, Peter Müller, editors

Label
Nonparametric Bayesian inference in biostatistics
Title
Nonparametric Bayesian inference in biostatistics
Statement of responsibility
Riten Mitra, Peter Müller, editors
Contributor
Editor
Subject
Genre
Language
eng
Summary
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
Member of
Cataloging source
N$T
Dewey number
570.1/5195
Illustrations
illustrations
Index
index present
LC call number
QH323.5
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorDate
1963 August 9-
http://library.link/vocab/relatedWorkOrContributorName
  • Mitra, Riten
  • Müller, Peter
Series statement
Frontiers in probability and the statistical sciences
http://library.link/vocab/subjectName
  • Biometry
  • Nonparametric statistics
  • Bayesian statistical decision theory
  • NATURE
  • SCIENCE
  • SCIENCE
  • Bayesian statistical decision theory
  • Biometry
  • Nonparametric statistics
  • Statistics
  • Statistics for Life Sciences, Medicine, Health Sciences
  • Biostatistics
  • Statistical Theory and Methods
  • Life sciences: general issues
  • Probability & statistics
Label
Nonparametric Bayesian inference in biostatistics, Riten Mitra, Peter Müller, editors
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-3-319-19518-6
Instantiates
Publication
Copyright
Note
Includes index
Antecedent source
unknown
Bibliography note
Includes bibliographical references at the end of each chapters and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
Dimensions
unknown
Extent
1 online resource (xvii, 448 pages)
File format
unknown
Form of item
online
Isbn
9783319195186
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
SpringerLink
Other control number
10.1007/978-3-319-19518-6
Other physical details
color illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)914706235
  • (OCoLC)ocn914706235
Label
Nonparametric Bayesian inference in biostatistics, Riten Mitra, Peter Müller, editors
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-3-319-19518-6
Publication
Copyright
Note
Includes index
Antecedent source
unknown
Bibliography note
Includes bibliographical references at the end of each chapters and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
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
Dimensions
unknown
Extent
1 online resource (xvii, 448 pages)
File format
unknown
Form of item
online
Isbn
9783319195186
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
SpringerLink
Other control number
10.1007/978-3-319-19518-6
Other physical details
color illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)914706235
  • (OCoLC)ocn914706235

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