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Edgeworth expansion in regression models

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  • Qumsiyeh, Maher B.

Abstract

Asymptotic expansions for the standardized as well as the studentized least squares estimate in multiple linear regression models are obtained without assuming normal errors and under simple assumptions that are easy to check.

Suggested Citation

  • Qumsiyeh, Maher B., 1990. "Edgeworth expansion in regression models," Journal of Multivariate Analysis, Elsevier, vol. 35(1), pages 86-101, October.
    • Handle: RePEc:eee:jmvana:v:35:y:1990:i:1:p:86-101
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    Citations

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    Cited by:

    1. Marcelo J. Moreira & Jack R. Porter & Gustavo A. Suarez, 2004. "Bootstrap and Higher-Order Expansion Validity When Instruments May Be Weak," NBER Technical Working Papers 0302, National Bureau of Economic Research, Inc.
    2. Robert Boik, 2008. "Accurate confidence intervals in regression analyses of non-normal data," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(1), pages 61-83, March.
    3. Moreira, Marcelo J. & Porter, Jack R. & Suarez, Gustavo A., 2009. "Bootstrap validity for the score test when instruments may be weak," Journal of Econometrics, Elsevier, vol. 149(1), pages 52-64, April.
    4. Ivanov, Alexander V. & Zwanzig, Silvelyn, 2002. "Saddlepoint Expansions in Linear Regression," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 183-207, October.
    5. Kakizawa, Yoshihide, 2009. "Third-order power comparisons for a class of tests for multivariate linear hypothesis under general distributions," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 473-496, March.
    6. Yanagihara, Hirokazu, 2003. "Asymptotic expansion of the null distribution of test statistic for linear hypothesis in nonnormal linear model," Journal of Multivariate Analysis, Elsevier, vol. 84(2), pages 222-246, February.

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