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Gordin's theorem and the periodogram

Published online by Cambridge University Press:  14 July 2016

Holger Rootzén*
Affiliation:
Tekniska Högskolan i Lund, Sweden

Abstract

In 1968 M. I. Gordin proved a very strong central limit theorem for stationary, ergodic sequences by means of approximation with martingales. In the present paper Gordin's theorem is generalized to cover also the periodogram of a stationary sequence, and the restriction of ergodicity is removed. It is noted that known central limit theorems for stationary processes can often be generalized to the periodogram by means of this result.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1976 

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References

[1] Billingsley, P. (1968) Convergence of Probability Measures. Wiley, New York.Google Scholar
[2] Eagleson, G. K. (1975a) On Gordin's central limit theorem for stationary processes. J. Appl. Prob. 12, 176179.Google Scholar
[3] Eagleson, G. K. (1975b) Martingale convergence to mixtures of infinitely divisible laws. Ann. Prob. 3, 557562.Google Scholar
[4] Gordin, M. I. (1969) The central limit theorem for stationary processes. Dokl. Akad. Nauk SSR 188, 11741176.Google Scholar
[5] Hannan, E. J. (1973) Central limit theorems for time series regression. Z. Wahrscheinlichkeitsth. 26, 157170.Google Scholar
[6] Heyde, C. C. (1974) On the central limit theorem for stationary processes. Z. Wahrscheinlichkeitsth. 30, 315320.Google Scholar
[7] Heyde, C. C. (1975) On the central limit theorem and iterated logarithm law for stationary processes. Bull. Austral. Math. Soc. 12, 18.Google Scholar
[8] Rootzén, H. (1976) Fluctuations of sequences which converge in distribution. Ann. Prob. 4.Google Scholar
[9] Rozanov, Yu. A. (1968) Stationary Random Processes. Holden Day, San Francisco.Google Scholar