On Fractal Distribution Function Estimation and Applications
UNIMI Economics Working Paper No. 07.2002
30 Pages Posted: 21 Nov 2004
Date Written: March 2002
Abstract
In this paper we review some recent results concerning the approximations of distribution functions and measures on [0,1] based on iterated function systems. The two different approaches available in the literature are considered and their relation are investigated in the statistical perspective. In the second part of the paper we propose a new class of estimators for the distribution function and the related characteristic and density functions. Glivenko-Cantelli, LIL properties and local asymptotic minimax efficiency are established for some of the proposed estimators. Via Monte Carlo analysis we show that, for small sample sizes, the proposed estimator can be as efficient or even better than the empirical distribution function and the kernel density estimator respectively. This paper is to be considered as a first attempt in the construction of new class of estimators based on fractal objects. Pontential applications to survival analysis with random censoring are proposed at the end of the paper.
Keywords: Fractals, estimation
JEL Classification: C13, C63
Suggested Citation: Suggested Citation