## Applied statistical decision theoryExperimentation and decision: general theory; Extensive-form analysis when sampling and terminal utilities are additive; Distribution theory. |

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20 pages matching **joint distribution** in this book

#### Page xxvi

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### Contents

The Problem and the Two Basic Modes of Analysis | 3 |

Combination of Formal and Informal Analysis | 17 |

Prior Weights and Consistent Behavior | 25 |

Copyright | |

23 other sections not shown

### Common terms and phrases

approximation assign Bernoulli process beta function beta-binomial binomial compute Conjugate prior cost cumulative function cumulative probabilities decision maker decision problem defined definition denote distribution with parameter estimate evaluated EVPI EVSI example expected terminal opportunity expected utility expected value experiment Figure gamma gamma-2 given h is known h is unknown Independent Normal process inverted-beta-1 joint density joint distribution kernel likelihood linear linear-loss integrals lt(a marginal density marginal distribution marginal likelihood mass function matrix mean and variance nondegenerate Normal distribution Normal-gamma normalized density function observations obtain optimal act optimal sample perfect information Poisson Poisson process positive-definite posterior distribution precision h preposterior analysis prior density prior distribution prior expected proof prove quantity random variable sample information scalar Section Substituting sufficient statistic Table terminal act terminal analysis terminal opportunity loss Theorem tion unconditional distribution univariate ut(a value of perfect vector write