Bayesian Analysis of the Independent Multi-normal Process--neither Mean nor Precision Known
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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. This work has been selected by scholars as being culturally importa...
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. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
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