Colin Mallows
Published 2007-08-08Version 1
Given samples (x_1,...,x_m) and (z_1,...,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.
Comments: Published at http://dx.doi.org/10.1214/074921707000000021 in the IMS Lecture Notes Monograph Series (http://www.imstat.org/publications/lecnotes.htm) by the Institute of Mathematical Statistics (http://www.imstat.org)
Journal: IMS Lecture Notes Monograph Series 2007, Vol. 54, 1-11
An optimal $(ε,δ)$-approximation scheme for the mean of random variables with bounded relative variance
Ergodicity of Fuzzy Markov Chains Based on Simulation Using Sequences
Lazy ABC
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