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Berry-Esseen Inequality for Unbounded Exchangeable Pairs

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Part of the book series: Lecture Notes in Statistics ((LNSP,volume 205))

Abstract

The Berry-Esseen inequality is well-established by the Stein method of exchangeable pair approach when the difference of the pair is bounded. In this paper we obtain a general result which can achieve the optimal bound under some moment assumptions. As an application, a Berry-Esseen bound of \(O(1/\sqrt{n})\) is derived for an independence test based on the sum of squared sample correlation coefficients.

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References

  1. Anderson TW (1984) An introduction to multivariate statistical analysis. 2nd edn. Wiley, New York.

    MATH  Google Scholar 

  2. Bai ZD, Saranadasa H (1996) Effect of high dimension: by an example of a two sample problem. Stat Sinica 6:311–329

    MATH  MathSciNet  Google Scholar 

  3. Barbour A, Chen LHY (2005) An introduction to Stein method. In: Lecture notes series 4, institute for mathematical sciences, Singapore University Press and World Scientific, National University of Singapore.

    Google Scholar 

  4. Chen LHY, Goldstein L, Shao QM (2010) Normal approximation by Stein’s method. 2nd edn. Springer, New York.

    Google Scholar 

  5. Chen LHY, Shao QM (2004) Normal approximation under local dependence. Ann Probab 32:1985–2028

    Article  MATH  MathSciNet  Google Scholar 

  6. Chen LHY, Shao QM (2005) Normal approximation. In: Barbour AD, Chen LHY (eds) An introduction to Stein’s method. Lecture notes series, institute for mathematical sciences, vol 4. World Scientific, NUS, pp 1–59

    Google Scholar 

  7. Chen S, Mudholkar GS (1989) A remark on testing significance of an observed correlation matrix. Aust J Stat 31:105–110

    Article  MATH  MathSciNet  Google Scholar 

  8. Chen S, Mudholkar GS (1990) Null distribution of the sum of squared z-transforms in testing complete independence. Ann Inst Stat Math 42:149–155

    Article  MATH  Google Scholar 

  9. Dempster AP (1958) A high dimensional two sample significance test. Ann Math Stat 29:995–1010

    Article  MATH  MathSciNet  Google Scholar 

  10. Dempster AP (1960) A significance test for the separation of two highly multivariate small samples. Biometrics 16:41–50

    Article  MATH  MathSciNet  Google Scholar 

  11. Diaconis P, Holmes S (2004) Stein’s method: expository lectures and applications. In: IMS Lecture notes, vol 46. Hayward, CA.

    Google Scholar 

  12. Fan JQ, Li R (2006). Statistical challenges with high dimensionality: Feature selection in knowledge discovery. In: Sanz-Sole M, Soria J, Varona JL, Verdera J (eds) Proceedings of the international congress of mathematicians, vol 3. pp 595–622

    Google Scholar 

  13. Jiang T (2004) The asymptotic distributions of the largest entries of sample correlation matrices. Ann Appl Probab 14:865–880

    Article  MATH  MathSciNet  Google Scholar 

  14. Ledoit O, Wolf M (2002) Some hypothesis tests for the covariance matrix when the dimention is lager comepared to the sample size. Ann Stat 30:1081–1102

    Article  MATH  MathSciNet  Google Scholar 

  15. Liu WD, Lin ZY, Shao QM (2008) The Asymptotic distribution and Berry-Esseen bound of a new test for independence in high dimension with an application to stochastic optimization. Ann Appl Probab 18:2337–2366

    Article  MATH  MathSciNet  Google Scholar 

  16. Maruyama Y (2007) On Srivastava’s multivariate sample skewness and kurtosis under non-normality . Stat Probab Lett 77:335–342

    Article  MATH  MathSciNet  Google Scholar 

  17. Morrison DF (2005) Multivariate Statistical Methods . 4th edn. Duxbury, Belmont CA

    Google Scholar 

  18. Nagao H (1973) On some test criteria for covariance matrix. Ann Stat 1:700–709

    Article  MATH  MathSciNet  Google Scholar 

  19. Rinott Y, Rotar V (1997) On coupling constructions and rates in the CLT for dependent summands with applications to the antivoter model and weighted U-statistics. Ann Appl Probab 7:1080–1105

    Article  MATH  MathSciNet  Google Scholar 

  20. Saranadasa H (1993) Asymptotic expansion of the misclassification probabilities of D- and A-criteria for discrimination from two high-dimensional populations using the theory of large-dimensional random matrice. J Mult Anal 46:154–174

    Article  MATH  MathSciNet  Google Scholar 

  21. Schott JR (2005) Testing for complete independence in high dimentions. Biometrika 92:951–956

    Article  MATH  MathSciNet  Google Scholar 

  22. Schott JR (2006) A high dimensional test for the equality of the smallest eigenvalues of a covariance matrix. J Mult Anal 97:827–843

    Article  MATH  MathSciNet  Google Scholar 

  23. Stein C (1986) Approximate computation of expectations. 2nd edn. IMS, Hayward

    MATH  Google Scholar 

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Acknowledgments

The second author is partially supported by Hong Kong RGC CERG 602608 and 603710.

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Correspondence to Yanchu Chen .

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Chen, Y., Shao, QM. (2012). Berry-Esseen Inequality for Unbounded Exchangeable Pairs. In: Barbour, A., Chan, H., Siegmund, D. (eds) Probability Approximations and Beyond. Lecture Notes in Statistics(), vol 205. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1966-2_2

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