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Validity Of Edgeworth Expansions For Statistics Of Time Series

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  • Masanobu Taniguchi

Abstract

. In this paper, we discuss the validity of the multivariate Edgeworth expansion of distribution functions of statistics which need not be standardized sums of independent and identically distributed vectors. We apply this result to statistics of time series. In particular, we shall give the asymptotic expansion of the distribution of the maximum likelihood estimator of a parameter of a circular autoregresive moving average process.

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  • Masanobu Taniguchi, 1984. "Validity Of Edgeworth Expansions For Statistics Of Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 5(1), pages 37-51, January.
    • Handle: RePEc:bla:jtsera:v:5:y:1984:i:1:p:37-51
    DOI: 10.1111/j.1467-9892.1984.tb00377.x
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    Cited by:

    1. D. S. Poskitt, 2008. "Properties of the Sieve Bootstrap for Fractionally Integrated and Non‐Invertible Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(2), pages 224-250, March.
    2. Poskitt, D.S. & Grose, Simone D. & Martin, Gael M., 2015. "Higher-order improvements of the sieve bootstrap for fractionally integrated processes," Journal of Econometrics, Elsevier, vol. 188(1), pages 94-110.
    3. Gubhinder Kundhi & Paul Rilstone, 2020. "Simplified Matrix Methods for Multivariate Edgeworth Expansions," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(2), pages 293-326, June.

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