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An urn model from learning theory
Author(s) -
Boucheron Stéphane,
Gardy Danièle
Publication year - 1997
Publication title -
random structures and algorithms
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.314
H-Index - 69
eISSN - 1098-2418
pISSN - 1042-9832
DOI - 10.1002/(sici)1098-2418(199701/03)10:1/2<43::aid-rsa3>3.0.co;2-x
Subject(s) - gaussian , convergence (economics) , limiting , mathematics , statistical physics , markov chain , gaussian process , mathematical economics , statistics , physics , engineering , economics , economic growth , mechanical engineering , quantum mechanics
We present an urn model that is a variation of the classical occupancy model, and in which the balls are of two types (good and bad). We analyze the number of urns that contain more (or fewer) good balls than bad balls. We find Gaussian limiting distributions in the static case and convergence of the finite‐dimensional distributions towards those of a Gaussian, non‐Markov process in the dynamic case. © 1997 John Wiley & Sons, Inc. Random Struct. Alg. , 10 , 43–67 (1997)