Journal of Applied Mathematics and Decision Sciences
Volume 2005 (2005), Issue 1, Pages 33-46
doi:10.1155/JAMDS.2005.33
Approximating distribution functions by iterated function systems
Department of Mathematics, University of Ulster, Ireland
Received 1 August 2003; Revised 24 January 2004
Copyright © 2005 Stefano Maria Iacus and Davide La Torre. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
An iterated function system (IFS) on the space of distribution functions is built with the aim of proposing a new class of distribution function estimators. One IFS estimator and its asymptotic properties are studied in detail. We also propose a density estimator derived from the IFS distribution function estimator by using Fourier
analysis. Relative efficiencies of both estimators, for small and moderate sample sizes, are presented via Monte Carlo analysis.