TY - CHAP A1 - Hongsheng Dai ED1 - Niansheng Tang Y1 - 2020-07-15 PY - 2020 T1 - A Review on the Exact Monte Carlo Simulation N2 - 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. BT - Bayesian Inference on Complicated Data SP - Ch. 3 UR - https://doi.org/10.5772/intechopen.88619 DO - 10.5772/intechopen.88619 SN - 978-1-83880-386-5 PB - IntechOpen CY - Rijeka Y2 - 2020-09-26 ER -