Bayesian missing data problems: EM, data augmentation and noniterative computation
Tan, Ming T.
creator
text
xxu
Boca Raton
2010
CRC Press
monographic
eng
xviii, 328 p
Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation presents solutions to missing data problems through explicit or noniterative sampling calculation of Bayesian posteriors. The methods are based on the inverse Bayes formulae discovered by one of the author in 1995. Applying the Bayesian approach to important real-world problems, the authors focus on exact numerical solutions, a conditional sampling approach via data augmentation, and a noniterative sampling approach via EM-type algorithms. (http://www.crcpress.com/product/isbn/9781420077490)
Bayesian statistical decision theory
Missing observations (Statistics)
519.542 T2B2
Chapman & Hall/CRC biostatistics series; 32
9781420077490
140323