Asymptotic Normality for Deconvolution Estimators of Multivariate Densities of Stationary Processes

AbstractWe consider the estimation of the multivariate probability density functions of stationary random processes from noisy observations. The asymptotic normality of kernel-type deconvolution estimators is established for various classes of mixing processes. Classes of noise characteristic functions both with algebraic and with exponential decay are studied