
Nonparametric Bayesian Inference in Biostatistics
Description
Alles über E-Books | Antworten auf Fragen rund um E-Books, Kopierschutz und Dateiformate finden Sie in unserem Info- & Hilfebereich.
More details
Other editions
Additional editions

Persons
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.
Content
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.
System requirements
File format: PDF
Copy protection: Watermark-DRM (Digital Rights Management)
System requirements:
- Computer (Windows; MacOS X; Linux): Use the free software Adobe Reader, Adobe Digital Editions, or any other PDF viewer of your choice (see eBook Help).
- Tablet/Smartphone (Android; iOS): Install the free app Adobe Digital Editions or another reading app for eBooks, e.g., PocketBook (see eBook Help).
- E-reader: Bookeen, Kobo, Pocketbook, Sony, Tolino and many more (only limited: Kindle).
The file format PDF always displays a book page identically on any hardware. This makes PDF suitable for complex layouts such as those used in textbooks and reference books (images, tables, columns, footnotes). Unfortunately, on the small screens of e-readers or smartphones, PDFs are rather annoying, requiring too much scrolling.
This eBook uses Watermark-DRM, a „soft” copy protection. This means that there are no technical restrictions to prevent illegal distribution. However, there is a personalised watermark embedded in the eBook that can be used to identify the purchaser of the eBook in the event of misuse and to provide evidence for legal purposes.
For more information, see our eBook Help page.