We study a sequential variance reduction technique for Monte Carlo estimation of functionals in Markov Chains. The method is based on designing sequential control variates using s...
One of the impediments to the wide dissemination of software estimation and measurement practices is the significant overhead imposed by these practices on the project and develop...
An m-sample semiparametric model in which the ratio of m - 1 probability density functions with respect to the mth is of a known parametric form without reference to any parametri...
Abstract--This paper studies the issue of optimal deconvolution density estimation using wavelets. The approach taken here can be considered as orthogonal series estimation in the ...
This paper describes a new kernel-based approach for linear system identification of stable systems. We model the impulse response as the realization of a Gaussian process whose s...