Nonparametric density estimation of streaming data using orthogonal series

Authors:
Kyle A. Caudle;Edward Wegman
Affiliations:
Department of Mathematics, U.S. Naval Academy, Annapolis, MD 21402, United States;Department of Computational and Data Sciences, George Mason University, Fairfax, VA 22030, United States
Venue:
Computational Statistics & Data Analysis
Year:
2009

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Abstract

Streaming data represent a serious challenge because implicit in the nature of streaming data, data are not exchangeable and are not storable. This means data must be processed on the fly. Density estimation is an essential tool used to make sense of data collected by large scale systems. In this paper, we present a recursive method for constructing and updating an estimate of the nonstationary probability density function. Our approach is shown to work well with simulated data as well as with real data.