Niansheng Tang

Yunnan University

Niansheng Tang is a Professor of Statistics and Dean of the School of Mathematics and Statistics, Yunnan University. He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of International Chinese Statistical Association (ICSA) in 2018, and IMS (Institute of Mathematical Statistics) Fellow in 2021. He obtained the National Science Foundation for Distinguished Young Scholars of China in 2012 and was awarded the Outstanding Service Award of the ICSA in 2018. He serves as a member of the editorial board for Statistics and Its Interface, Journal of Systems Science and Complexity, BMC Medical Research Methodology. He is also an Editor in Field for Communications in Mathematics and Statistics. His research interests include data clustering, biostatistics, Bayesian statistics, missing data analysis, statistical diagnosis, variable selection, high-dimensional data analysis, tensor data analysis, differential privacy, deep learning. He has published more than 175 research papers and authored four books.

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Latest work with IntechOpen 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.

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