Abstract #300808


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JSM 2002 Abstract #300808
Activity Number: 71
Type: Contributed
Date/Time: Monday, August 12, 2002 : 8:30 AM to 10:20 AM
Sponsor: Section on Nonparametric Statistics*
Abstract - #300808
Title: Non-parametric Density Estimation Via Wavelets
Author(s): Ren Zhang*+ and Lawrence Brown
Affiliation(s): University of Pennsylvania and University of Pennsylvania
Address: 3000 SH-DH, Univ. of Pennsylvania, Philadelphia, Pennsylvania, 19104, US
Keywords: Non-parametric ; wavelet ; density ; root-unroot
Abstract:

A new methodology for the application of wavelets in non-parametric density estimation is proposed. It transfers a density estimation problem into a regression problem by binning the observations and then treating the square root of the observation counts as the new data for regression. It then uses a wavelet regression method to recover the square root of the density. Because of the automatic adaptivity of wavelets methods, this density estimation method achieves the optimal convergence rate and is computationally efficient. Data from the call service center of a large northeast bank is used to demonstrate the usage of this method for practical problems. In this setting, the density estimator is used to describe the arrival rate of the phone call as a function of covariates such as time-of-day and day of the week.


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