Applied Statistical Decision TheoryDivision of Research, Graduate School of Business Adminitration, Harvard University, 1961 - Business & Economics - 356 pages "In the field of statistical decision theory, Raiffa and Schlaifer have sought to develop new analytic techniques by which the modern theory of utility and subjective probability can actually be applied to the economic analysis of typical sampling problems." --From the foreword to their classic work "Applied Statistical Decision Theory," First published in the 1960s through Harvard University and MIT Press, the book is now offered in a new paperback edition from Wiley |
Contents
The Problem and the Two Basic Modes of Analysis | 3 |
Univariate Normalized Mass and Density Functions | 7 |
Sufficient Statistics and Noninformative Stopping | 28 |
Copyright | |
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Common terms and phrases
a₁ a₂ approximation assign Bernoulli process beta function beta-binomial binomial choose compute conditional measure conjugate Conjugate prior cost cumulative function data-generating process decision maker decision problem definition denote estimate evaluated EVPI EVSI example expected terminal opportunity expected utility expected value experiment experimental outcome extensive form Ezle Figure follows gamma gamma function gamma-1 given h is known h is unknown k₁ k₂ kernel li(e likelihood linear linear-loss integrals marginal measure matrix mean n₁ normalized density function observed obtain optimal act optimal sample parameter perfect information Poisson possible posterior density posterior distribution preposterior analysis prior density prior distribution prior expected probability quantity random variable Section stopping process Substituting sufficient statistic Table terminal act terminal analysis terminal opportunity loss terminal utility theorem tion u₁ u₁(a value of perfect variance vector vi(e