Spectral Analysis with Randomly Missed Observations: The Binomial Case

Abstract

Estimation of the spectral density of a discrete stationary process is considered under the assumption that some of the observations are missing due to some binomially distributed random mechanism. The asymptotic variance of the estimate is derived for normally distributed random variables. As in the author's dissertation [7], the extension to processes which are stationary of fourth order is fairly standard. It is hoped that one will be able to extend these results to more complicated random mechanisms.