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MISSING DATA ANALYSIS IN CYCLOSTATIONARY MODELS

Data publikacji: 09.02.2015

Czasopismo Techniczne, 2014, Nauki Podstawowe Zeszyt 2 NP (16) 2014, s. 25 - 36

https://doi.org/10.4467/2353737XCT.14.297.3385

Autorzy

,
Christiana Drake
Department of Statistics, University of California, Davis
Wszystkie publikacje autora →
,
Oskar Knapik
CREATES, Department of Economics and Business, Aarhus University
Wszystkie publikacje autora →
Jacek Leśków
Institute of Mathematics, Cracow University of Technology
Wszystkie publikacje autora →

Tytuły

MISSING DATA ANALYSIS IN CYCLOSTATIONARY MODELS

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.

Bibliografia

Brockwell P.J., Davis R.A., Introduction to time series and forecasting, Springer, 2002.

Dempster A.P., Laird N.M. and Rubin D.B., Maximum Likelihood from Incomplete Data via The EM Algorithm (with discussion), J. Roy. Statist. Soc. B, Vol. 39, 1977, 1—38.

Galbraith R.F., Galbraith J.I., On the inverses of some patterned matrices arising in the theory of stationary time series, Journal of Applied Probability, Vol. 11, 1974, 63—71.

Gardner W.A., Representation and estimation of cyclostationary processes, IEEE Transactions on Information Theory, Vol. 19, No. 3, 1973, 375—376.

Gardner W.A., Napolitano A., Paura L., Cyclostationarity: Half a century of research, Signal Processing, Vol. 86, No. 4, 2006, 639—697.

Giannakis,G.B, Dandawate, A.V., Consistent Kth-order time-frequency representations for (almost) cyclostationary signals, in: IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis, Victoria, BC, Canada, 79 October 1992, 123—126.

Ghogho, M., Garel, B., Maximum likelihood estimation of amplitude-modulated time series, Signal Processing, Vol. 75, 1999 99—116.

Hamilton J.D., Time Series Analysis, Princeton University Press, 1994.

Hurd H. L., Miamee A., Periodically Correlated Random Sequences: Spectral Theory and Practice (Wiley Series in Probability and Statistics), Wiley-Interscience, 2007.

Little R.J.A., Rubin D.B., Statistical Analysis with Missing Data. John Wiley & Sons, New York, 2nd edn., 2002.

Schaffer J.L., Analysis of Incomplete Multivariate Data. Chapman & Hall/CRC, 1997.

Stefanakos Ch.N., Athanassoulis G.A., A unified methodology for the analysis, completion and simulation of nonstationary time series with missing values, with application to wave data, Applied Ocean Research, Vol. 23, Issue 4, 2001, 207—220.

Verbyla A.P., A note on the inverse covariance matrix of the autoregressive process, Australian Journal of Statistics, Vol. 27, Issue 2, 1985, 221—224.

Wu C.F.J., On the convergence properties of the EM algorithm, Annals of Statistics, Vol. 11, 1983, 95—103.

Informacje

Informacje: Czasopismo Techniczne, 2014, Nauki Podstawowe Zeszyt 2 NP (16) 2014, s. 25 - 36

Typ artykułu: Oryginalny artykuł naukowy

Tytuły:

Polski:

MISSING DATA ANALYSIS IN CYCLOSTATIONARY MODELS

Angielski:

MISSING DATA ANALYSIS IN CYCLOSTATIONARY MODELS

Autorzy

Department of Statistics, University of California, Davis

CREATES, Department of Economics and Business, Aarhus University

Institute of Mathematics, Cracow University of Technology

Publikacja: 09.02.2015

Status artykułu: Otwarte __T_UNLOCK

Licencja: Żadna

Udział procentowy autorów:

Christiana Drake (Autor) - 33%
Oskar Knapik (Autor) - 33%
Jacek Leśków (Autor) - 34%

Korekty artykułu:

-

Języki publikacji:

Angielski

Liczba wyświetleń: 1696

Liczba pobrań: 1072

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