Bayesian missing data problems: EM, data augmentation and noniterative computation

This book provides a systematic view of Bayesian methods to be used with missing data problems. The text presents a non-iterative approach that provides either explicit or non-iterative sampling calculation of posteriors. This computation includes exact numerical solutions, a conditional sampling approach via data augmentation, and a non-iterative sampling approach via EM-type algorithms. It illustrates the application of Bayesian analysis to important biostatistics problems and to other real-world applications, including the constrained parameter problem reformulated as a missing data problem. The text includes S-PLUS/R computer codes.

• ISBN: 978-1-4200-7749-0
• Editorial: Chapman & Hall/CRC Statistics and Mathem
• Encuadernacion: Cartoné
• Páginas: 344
• Fecha Publicación: 24/08/2009
• Nº Volúmenes: 1
• Idioma: Inglés