Applied Statistical Decision Theory

a₁ approximation assign assumption 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-2 given h is known h is unknown kernel likelihood linear linear-loss integrals marginal measure matrix maxa mean n₁ normalized density function observations obtain optimal act optimal sample parameter perfect information Poisson possible posterior density posterior distribution preposterior analysis prior density prior distribution prior expected probability Pzle quantity random variable result Section stopping process substituting sufficient statistic Table terminal act terminal analysis terminal opportunity loss terminal utility theorem tion value of perfect variance vector κι(α μι ρη