Subjective Probability Models for Lifetimes, Vol. 91 FROM THE PUBLISHER
"Bayesian methods in reliability cannot be fully utilized and understood without full comprehension of the essential differences that exist between frequentist probability and subjective probability. Switching from the frequentist to the subjective approach requires that some fundamental concepts be rethought and suitably redefined." "Subjective Probability Models for Lifetimes details those differences and clarifies aspects of subjective probability that have a direct influence on modeling and drawing inference from failure and survival data. In particular, without a framework of Bayesian theory, the author considers the effects of different levels of information in the analysis of the phenomena of positive and negative aging." "The author coherently reviews and compares the various definitions and results concerning stochastic ordering, statistical dependence, reliability, and decision theory. Keeping the mathematical difficulty at a reasonable level, he offers a detailed treatment of different aspects of probability distributions for exchangeable vectors of lifetimes. This approach imparts a clear understanding of what the "probabilistic description of aging" really is, and why it is important to analyzing survival and failure data. Examples and exercises reinforce that understanding and new results suggest directions for future research."--BOOK JACKET.
FROM THE CRITICS
Booknews
Spizzichino (U. La Sapienza) presents a text for statisticians, probabilists, and engineers. Coverage includes the impact of subjective probability on the language and formalization of statistics and the related role of exchangeable random variables; fundamental notions of multivariate probability calculus for non-negative random variables; some notions of stochastic dependence, aging, and their mutual relations; the probabilistic meaning of distributions with Schur-constant, Schur-concave and Schur-convex survival functions or density functions; and Bayesian decisions, orderings, and majorization. The reader is assumed to have a background in calculus in several variables, basic theory of probability at an intermediate level, fundamentals of Bayesian statistics, basic elements of stochastic processes, reliability, and life testing at an introductory level. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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