非实体
发表于 2025-3-23 12:43:48
Convergence,For example, if we assume that a penny has probability 1/2 of coming down heads on each toss, and that the different tosses are independent, it follows that the limiting proportion of heads will be 1/2 almost surely.
军械库
发表于 2025-3-23 16:01:09
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变白
发表于 2025-3-23 19:15:26
Robustness of Bayes Methods,ions about a probability model {..,.∈.} for the observations in Y, and about a loss function . connecting the decision and unknown parameter value. In Bayesian statistics, there is in addition an assumed prior distribution.
AFFIX
发表于 2025-3-23 22:37:03
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Negotiate
发表于 2025-3-24 03:19:16
Lecture Notes in Computer ScienceKolmogorov’s exquisite formalization of conditional probability in the unitary case (1933) does not readily generalize to non-unitary probabilities. Stone and Dawid (1972) show one type of difficulty with their marginalization paradoxes for improper priors.
独轮车
发表于 2025-3-24 07:08:37
Stefan Bauer,Edward W.N. BernroiderThe essence of Bayes theory is giving probability values to bets. Methods of generating such probabilities are what separate the various theories.
modest
发表于 2025-3-24 12:29:19
Erratum to: Human Aspects of VisualizationLet . be a probability on ., and choose a unitary probability . on . to minimize the information .(log(.)) subject to ....., . 1,..., .. The optimal probability . has density
极小量
发表于 2025-3-24 14:52:15
Human Assessment and Cultural FactorsGiven X, suppose ., and the .. are independent. The straight estimate .. of .. is least squares, maximum likelihood, of minimum variance among unbiased estimators, posterior means with respect to the Jeffreys density (the ..,..., .. are uniform) but for all these virtues inadmissible with loss function .for . > 2, Stein (1956).
祖先
发表于 2025-3-24 19:03:51
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边缘带来墨水
发表于 2025-3-25 02:10:49
Human Assessment: Cognition and MotivationWhereas Bayes procedures require detailed probability models for observations and parameters, nonparametric procedures work with a minimum of probabilistic assumptions. It is therefore of interest to examine nonparametric problems from a Bayesian point of view.