Bayesian Inference on Complicated Data

Niansheng Tang

ISBN 10: 1838803858 / ISBN 13: 9781838803858

Published by Intechopen Jul 2020, 2020

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Due to great applications in various fields, such as social science, biomedicine, genomics, and signal processing, and the improvement of computing ability, Bayesian inference has made substantial developments for analyzing complicated data. This book introduces key ideas of Bayesian sampling methods, Bayesian estimation, and selection of the prior. It is structured around topics on the impact of the choice of the prior on Bayesian statistics, some advances on Bayesian sampling methods, and Bayesian inference for complicated data including breast cancer data, cloud-based healthcare data, gene network data, and longitudinal data. This volume is designed for statisticians, engineers, doctors, and machine learning researchers.Books on Demand GmbH, Überseering 33, 22297 Hamburg 118 pp. Englisch.

Seller Inventory # 9781838803858

Bibliographic Details

• Title: Bayesian Inference on Complicated Data
• Publisher: Intechopen Jul 2020
• Publication Date: 2020
• Language: English
• ISBN 10: 1838803858
• ISBN 13: 9781838803858
• Binding: Buch
• Condition: Neu
• Dimensions: 266W x 185H x 13D millimeters 266 millimeters width by 185 millimeters height by 13 millimeters depth
• Weight: 477 grams

About this title

Synopsis

Due to great applications in various fields, such as social science, biomedicine, genomics, and signal processing, and the improvement of computing ability, Bayesian inference has made substantial developments for analyzing complicated data. This book introduces key ideas of Bayesian sampling methods, Bayesian estimation, and selection of the prior. It is structured around topics on the impact of the choice of the prior on Bayesian statistics, some advances on Bayesian sampling methods, and Bayesian inference for complicated data including breast cancer data, cloud-based healthcare data, gene network data, and longitudinal data. This volume is designed for statisticians, engineers, doctors, and machine learning researchers.