DocumentCode :
941460
Title :
Recursive probability density estimation for weakly dependent stationary processes
Author :
Masry, Elias
Volume :
32
Issue :
2
fYear :
1986
fDate :
3/1/1986 12:00:00 AM
Firstpage :
254
Lastpage :
267
Abstract :
Recursive estimation of the univariate probability density function 
for stationary processes 
is considered. Quadratic-mean convergence and asymptotic normality for density estimators 
are established for strong mixing and for asymptotically uncorrelated processes . Recent results for nonrecursive density estimators are extended to the recursive case.
for stationary processes is considered. Quadratic-mean convergence and asymptotic normality for density estimators are established for strong mixing and for asymptotically uncorrelated processes . Recent results for nonrecursive density estimators are extended to the recursive case.Keywords :
Probability; Recursive estimation; Bandwidth; Convergence; Helium; Kernel; Markov processes; Pattern recognition; Probability density function; Recursive estimation;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1986.1057163
Filename :
1057163
Link To Document :
