MISSING DATA ANALYSIS IN CYCLOSTATIONARY MODELS

Christiana Drake,

Oskar Knapik,

Jacek Leśków

Abstrakt

In recent years, there has been a growing interest in modeling cyclostationary time series. The survey of Gardner and others [5] is quoting over 1500 different recently published papers that are dedicated to this topic. Data that can be reasonable modeled with such time series is often incomplete. To our knowledge, no systematic research has been conducted on that problem. This paper attempts to fill this gap. In this paper we propose to use EM algorithms to extend estimation for situation when some observations are missing.

Słowa kluczowe: (almost) periodically correlated time series, cyclostationary signals, EM algorithm, missing data
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