*Edited by Niansheng Tang*

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.

ISBN 978-1-83880-385-8

Bayesian Inference on Complicated Data

Published in London, UK © 2020 IntechOpen © spainter\_vfx / iStock

## Bayesian Inference on Complicated Data

*Edited by Niansheng Tang*

## Bayesian Inference on Complicated Data

*Edited by Niansheng Tang*

Published in London, United Kingdom

### *Supporting open minds since 2005*

Bayesian Inference on Complicated Data http://dx.doi.org/10.5772/intechopen.83214 Edited by Niansheng Tang

#### Contributors

Ying-Ying Zhang, Hongsheng Dai, Christophe Ley, Fatemeh Ghaderinezhad, Xi Chen, Jianhua Xuan, Catherine C. Liu, Junshan Shen, Michelle Yongmei Wang, Trevor Park, Shahid Naseem

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First published in London, United Kingdom, 2020 by IntechOpen IntechOpen is the global imprint of INTECHOPEN LIMITED, registered in England and Wales, registration number: 11086078, 7th floor, 10 Lower Thames Street, London, EC3R 6AF, United Kingdom Printed in Croatia

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Bayesian Inference on Complicated Data Edited by Niansheng Tang p. cm. Print ISBN 978-1-83880-385-8 Online ISBN 978-1-83880-386-5 eBook (PDF) ISBN 978-1-83962-704-0
