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Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 124))

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Abstract

We define generalized self-normalized sums as t-type statistics with flexible norming sequence in the denominator. It will be shown how Edgeworth expansions can be utilized to provide a full characterization of asymptotic crossing points (ACPs) between the density of such generalized self-normalized sums and the standard normal density. Although the proof of our main ACP theorem is self-contained, we also draw connections to related expansions for the cumulative distribution function of generalized self-normalized sums that we have derived in previous work.

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References

  1. Finner, H., Roters, M., Dickhaus, T.: Characterizing density crossing points, extended online version (2007). Available via http://www.helmut-finner.de/Density_Crossing_Points.pdf

  2. Finner, H., Roters, M., Dickhaus, T.: Characterizing density crossing points. Am. Stat. 61(1), 28–33 (2007)

    Article  MathSciNet  Google Scholar 

  3. Student: The probable error of a mean. Biometrika 6, 1–25 (1908)

    Google Scholar 

  4. Hall, P.: The Bootstrap and Edgeworth Expansion. Springer Series in Statistics. Springer, New York (1992)

    Book  MATH  Google Scholar 

  5. Hsu, P.: The approximate distributions of the mean and variance of a sample of independent variables. Ann. Math. Stat. 16, 1–29 (1945)

    Article  MathSciNet  MATH  Google Scholar 

  6. Chung, K.-L.: The approximate distribution of Student’s statistic. Ann. Math. Stat. 17, 447–465 (1946)

    Article  MATH  Google Scholar 

  7. Hall, P.: Edgeworth expansion for Student’s t statistic under minimal moment conditions. Ann. Probab. 15, 920–931 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  8. Kabaila, P.: A method for the computer calculation of edgeworth expansions for smooth function models. J. Comput. Graph. Stat. 2(2), 199–207 (1993)

    Google Scholar 

  9. Finner, H., Dickhaus, T.: Edgeworth expansion for normalized sums: Chung’s 1946 Method Revisited. Stat. Probab. Lett. 80(23–24), 1875–1880 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  10. Lehmann, E.L., Romano, J.P.: Testing Statistical Hypotheses, 3rd edn. Springer Texts in Statistics. Springer, New York (2005)

    MATH  Google Scholar 

  11. Sansing, R., Owen, D.: The density of the t-statistic for non-normal distributions. Commun. Stat. 3, 139–155 (1974)

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Thorsten Dickhaus .

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Dickhaus, T., Finner, H. (2016). Asymptotic Density Crossing Points of Self-Normalized Sums and Normal. In: Chen, K., Ravindran, A. (eds) Forging Connections between Computational Mathematics and Computational Geometry. Springer Proceedings in Mathematics & Statistics, vol 124. Springer, Cham. https://doi.org/10.5176/2251-1911_CMCGS14.02_17

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