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An introduction to probability theory and its applications
William Feller
- 01 Jan 1950
32.2K
About: The article was published on 01 Jan 1950. and is currently open access. The article focuses on the topics: Probability and statistics & Imprecise probability.
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Citations
Channel Coding Rate in the Finite Blocklength Regime
TL;DR: It is shown analytically that the maximal rate achievable with error probability ¿ isclosely approximated by C - ¿(V/n) Q-1(¿) where C is the capacity, V is a characteristic of the channel referred to as channel dispersion, and Q is the complementary Gaussian cumulative distribution function.
•Book
A Probabilistic Theory of Pattern Recognition
Luc Devroye,László Györfi,Gábor Lugosi +2 more
- 01 Jan 1996
TL;DR: The Bayes Error and Vapnik-Chervonenkis theory are applied as guide for empirical classifier selection on the basis of explicit specification and explicit enforcement of the maximum likelihood principle.
Increasing risk: I. A definition
TL;DR: The authors tried to answer the question: When is a random variable Y "more variable" than another random variable X "less variable" by asking when a variable X is more variable than another variable Y.
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On the number of segregating sites in genetical models without recombination.
TL;DR: The distribution is obtained for the number of segregating sites observed in a sample from a population which is subject to recurring, new, mutations but not subject to recombination, and applies approximately to three population models.
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Reaching a Consensus
TL;DR: In this article, the authors consider a group of individuals who must act together as a team or committee, and assume that each individual in the group has his own subjective probability distribution for the unknown value of some parameter.
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