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Edgeworth Expansions in Gaussian Autoregression

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  • Patrick Marsh

Abstract

We consider the construction of valid Edgeworth expansions for statistics arising in the context of Gaussian autoregression. By exploiting the properties of exponential families (to which these models belong), validity, of any order, is routinely established for a wide class of statistics.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Patrick Marsh, "undated". "Edgeworth Expansions in Gaussian Autoregression," Discussion Papers 00/58, Department of Economics, University of York.
    • Handle: RePEc:yor:yorken:00/58
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    References listed on IDEAS

    as
    1. Yoshihide Kakizawa, 1999. "Valid Edgeworth Expansions of Some Estimators and Bootstrap Confidence Intervals in First‐order Autoregression," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(3), pages 343-359, May.
    2. Taniguchi, M. & Watanabe, Y., 1994. "Statistical Analysis of Curved Probability Densities," Journal of Multivariate Analysis, Elsevier, vol. 48(2), pages 228-248, February.
    3. Phillips, Peter C B, 1977. "Approximations to Some Finite Sample Distributions Associated with a First-Order Stochastic Difference Equation," Econometrica, Econometric Society, vol. 45(2), pages 463-485, March.
    4. Satchell, Stephen Ellwood, 1984. "Approximation to the Finite Sample Distribution for Nonstable First Order Stochastic Difference Equations," Econometrica, Econometric Society, vol. 52(5), pages 1271-1289, September.
    5. Yoshimichi Ochi, 1983. "Asymptotic Expansions For The Distribution Of An Estimator In The First‐Order Autoregressive Process," Journal of Time Series Analysis, Wiley Blackwell, vol. 4(1), pages 57-67, January.
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