Open Access
VOL. 54 | 2007 Deconvolution by simulation
Colin Mallows

Editor(s) Regina Liu, William Strawderman, Cun-Hui Zhang

IMS Lecture Notes Monogr. Ser., 2007: 1-11 (2007) DOI: 10.1214/074921707000000021

Abstract

Given samples $(x_1,\ldots,x_m)$ and $(z_1, \ldots,z_n)$ which we believe are independent realizations of random variables $X$ and $Z$ respectively, where we further believe that $Z = X + Y$ with $Y$ independent of $X$, the problem is to estimate the distribution of $Y$. We present a new method for doing this, involving simulation. Experiments suggest that the method provides useful estimates.

Information

Published: 1 January 2007
First available in Project Euclid: 4 December 2007

MathSciNet: MR2459175

Digital Object Identifier: 10.1214/074921707000000021

Subjects:
Primary: 60J10 , 62G05 , 94C99

Keywords: Markov chains , nonparametric estimation

Rights: Copyright © 2007, Institute of Mathematical Statistics

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