DocumentCode :
1343110
Title :
Density estimation from an individual numerical sequence
Author :
Nobel, Andrew B. ; Morvai, Gusztav ; Kulkarni, Sanjeev R.
Author_Institution :
Dept. of Stat., North Carolina Univ., Chapel Hill, NC, USA
Volume :
44
Issue :
2
fYear :
1998
fDate :
3/1/1998 12:00:00 AM
Firstpage :
537
Lastpage :
541
Abstract :
This paper considers estimation of a univariate density from an individual numerical sequence. It is assumed that (1) the limiting relative frequencies of the numerical sequence are governed by an unknown density, and (2) there is a known upper bound for the variation of the density on an increasing sequence of intervals. A simple estimation scheme is proposed, and is shown to be L1 consistent when (1) and (2) apply. In addition, it is shown that there is no consistent estimation scheme for the set of individual sequences satisfying only condition (1)
Keywords :
estimation theory; parameter estimation; probability; sequences; signal sampling; statistical analysis; L1 consistent estimation; ergodic sample; individual numerical sequence; limiting relative frequencies; probability; statistics; univariate density estimation; upper bound; Convergence; Frequency; Histograms; Kernel; Nearest neighbor searches; Spline; Statistical distributions; Statistics; Stochastic processes; Upper bound;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/18.661503
Filename :
661503
Link To Document :
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