Strong consistency and rates for deconvolution of multivariate densities of stationary processes

Elias Masry

Stochastic Processes and their Applications, 1993, vol. 47, issue 1, 53-74

Abstract: We consider the estimation of the multivariate probability density functions of stationary random processes from noisy observations. The strong consistency and almost sure convergence rates for kernel-type deconvolution estimators is established for strongly mixing processes. The dependence of the a.s. convergence rates on the noise distribution is examined; both ordinary and super smooth noise distributions are considered.

Keywords: deconvolution; of; multivariate; densities; strongly; mixing; processes; almost; sure; convergence; rates (search for similar items in EconPapers)
Date: 1993
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Citations: View citations in EconPapers (17)

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