DocumentCode
910937
Title
Estimation of probability density and distribution functions
Author
Kashyap, R.L. ; Blaydon, Colin C.
Volume
14
Issue
4
fYear
1968
fDate
7/1/1968 12:00:00 AM
Firstpage
549
Lastpage
556
Abstract
First- and second-order stochastic gradient algorithms are developed for suitably approximating the unknown density and distribution functions of a random vector from a sequence of independent samples. The mean-square-error criterion and the integral-square-error criterion are used in the approximations. The rates of convergence and the approximation error are also evaluated.
Keywords
Estimation; Probability functions; Stochastic approximation; Approximation algorithms; Approximation error; Contracts; Convergence; Density functional theory; Distributed computing; Distribution functions; Pattern classification; Probability distribution; Stochastic processes;
fLanguage
English
Journal_Title
Information Theory, IEEE Transactions on
Publisher
ieee
ISSN
0018-9448
Type
jour
DOI
10.1109/TIT.1968.1054184
Filename
1054184
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