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原文連結
論文資訊
- 類型：已發表論文
- 日期：2013-10-31
摘要
We consider 貝氏 estimation of 資訊-theoretic quantities from data, using a Dirichlet prior. Acknowledging the uncertainty of the event space size m and the Dirichlet prior's concentration parameter c, we treat both as random variables set by a hyperprior. We show that the associated hyperprior, P (c; m), obeys a simple "Irrelevance of Unseen Variables" (IUV) desideratum iff P (c; m) = P (c) P (m). Thus, requiring IUV greatly reduces the number of degrees of freedom of the hyperprior. Some 資訊-theoretic quantities can be expressed multiple ways, in terms of different event spaces, e. g., mutual 資訊. With all hyperpriors (implicitly) used in earlier work, different choices of this event space lead to different posterior expected values of these 資訊-theoretic quantities. We show that there is no su
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