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Statistical decision theory and bayesian analysis by James O. Berger

Statistical decision theory and bayesian analysis James O. Berger ebook
Publisher: Springer
Page: 316
Format: djvu
ISBN: 0387960988, 9780387960982

It is one of the first comprehensive models that combine statistical decision theory in form of Bayesian analysis with a real options framework for projects exposed to different sources of uncertainty. Statistical Decision Theory: Estimation, Testing, and Selection. I'll recommend a book I find canonical that covers the philosophical and practical problems of hypothesis testing quite well and in depth: Statistical Decision Theory and Bayesian Analysis by J.O. The book is self-contained as it. No subjective decisions need to be involved. The use of Bayesian probabilities as the basis of Bayesian inference has been supported by several arguments, such as the Cox axioms, the Dutch book argument, arguments based on decision theory and de Finetti's theorem. Berger: Statistical Decision Theory and Bayesian Analysis (Springer, New York, 1985) 2nd ed. Smith: Bayesian Theory (Wiley, New York, 1994). Berger, amazon.com/gp/product/1441930744. In the objectivist stream, the statistical analysis depends on only the model assumed and the data analysed. In contrast, "subjectivist" statisticians deny the Justification of Bayesian probabilities.