This book provides an in-depth analysis of successive sample moment estimators and their properties. It covers the main principles behind moment estimators and provides detailed algorithms for calculating them. This book is essential for statisticians and data analysis professionals.
This essential text explores the Bayesian analysis of independent multi-normal processes when neither the mean nor the precision is known. Written by two of the most renowned mathematicians in the field, this book offers readers a comprehensive and accessible introduction to the challenges and opportunities of this exciting area of research. Featuring numerous exercises, examples, and real-world case studies, this book is an essential resource for anyone interested in the study of multi-normal processes and Bayesian inference.