Skip to main content

An Introduction to Normal Approximation

  • Chapter
  • First Online:
Rabi N. Bhattacharya

Part of the book series: Contemporary Mathematicians ((CM))

  • 1132 Accesses

Abstract

Normal approximation or, more generally the asymptotic theory, plays a fundamental role in the developments of modern probability and statistics. The one-dimensional central limit theorem and the Edgeworth expansion for independent real-valued random variables are well studied. We refer to the classical book by Petrov (1995). In the context of the multi-dimensional central limit theorem, Rabi Bhattacharya has made fundamental contributions to asymptotic expansions. The book by Bhattacharya and Ranga Rao (1976) is a standard reference. In this note I shall focus on two of his seminal papers (1975, 1977) on asymptotic expansions. Recent developments on normal approximation by Stein’s method and strong Gaussian approximation will also be discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. V. Bentkus (2003). On the dependence of the Berry-Esseen bound on dimension. J. Statist. Plann. Inf. 113, 385–402.

    Google Scholar 

  2. R.N. Bhattacharya (1968). Berry-Esseen bounds for the multi-dimensional central limit theorem. Bull. Amer. Math. Soc. 74, 285–287.

    Google Scholar 

  3. R.N. Bhattacharya (1975). On errors of normal approximation. Ann. Probab. 3, 815–828.

    Google Scholar 

  4. R.N. Bhattacharya (1977). Refinements of the multidimensional central limit theorem and applications. Ann. Probab. 5., 1–27.

    Google Scholar 

  5. R.N. Bhattacharya (1987). Some aspects of Edgeworth expansions in statistics and probability. New perspectives in theoretical and applied statistics. (Bilbao, 1986), 157–170. Wiley Ser. Probab. Math. Statist. Probab. Math. Statist., Wiley, New York

    Google Scholar 

  6. R.N. Bhattacharya and J.K. Ghosh (1988). On moment conditions for valid formal Edgeworth expansions. J. Multivariate Anal. 27, 68–79.

    Google Scholar 

  7. R.N. Bhattacharya and S. Holmes (2010). An exposition of Götze’s estimation of the rate of convergence in the multivariate central limit theorem. arXiv:1003.4254v1

    Google Scholar 

  8. R.N. Bhattacharya and R. Ranga Rao (1976). Normal Approximation and Asymptotic Expansions. Wiley, New York.

    Google Scholar 

  9. S. Chatterjee (2014). A short survey of Stein’s method. To appear in Proceedings of ICM 2014. arXiv:1404.1392

    Google Scholar 

  10. S. Chatterjee and E. Meckes (2008). Multivariate normal approximation using exchangeable pairs. ALEA. Latin American J. Probab. Statist. 4, 257–283.

    Google Scholar 

  11. L.H.Y. Chen, L. Goldstein and Q.M. Shao (2011). Normal Approximation by Stein’s Method. Spinger-Verlag, Berlin.

    Google Scholar 

  12. L.H.Y. Chen and X. Fang (2011). Multivariate normal approximation by Stein’s method: The concentration inequality approach. arXiv:1111.4073

    Google Scholar 

  13. L.H.Y. Chen, X. Fang and Q.M. Shao (2013). From Stein indentities to moderate deviations. Ann. Probab. 41, 262–293.

    Google Scholar 

  14. L.H.Y. Chan and Q.M. Shao (2001). A non-uniform Berry-Esseen bound via Stein’s method. Probab. Theory Related Fields 120, 236–254.

    Google Scholar 

  15. L.H.Y. Chan and Q.M. Shao (2004). Normal approximation under local dependence. Ann. Probab. 32, 1985–2028.

    Google Scholar 

  16. V. Chernozhukov, D. Chetverikov and K. Kato (2013). Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors. Ann. Statist. 41, 2786–2819.

    Google Scholar 

  17. V. Chernozhukov, D. Chetverikov and K. Kato (2014). Gaussian approximation of suprema of empirical processes. Ann. Statist. 42, 1564–1597.

    Google Scholar 

  18. G. Reinert and A. Röllin (2009). Multivariate normal approximation with Stein’s method of exchangeable pairs under a general linearity condition. Ann. Probab. 37, 2150–2173.

    Google Scholar 

  19. F. Götze (1991). On the rate of convergence in the multivariate CLT. Ann. Probab. 19, 724–739.

    Google Scholar 

  20. F. Götze and C. Hipp (1983). Asymptotic expansions for sums of weakly dependent random vectors. Z. Wahrsch. verw. Gebiete 64, 211–239.

    Google Scholar 

  21. Z.Y. Lin and W.D. Liu (2009). On maxima of periodograms of stationary processes. Ann. Statisit. 37, 2676–2695.

    Google Scholar 

  22. W.D. Liu and Q.M. Shao (2013), A Cramér moderate deviation theorem for Hotelling T 2-statistic with applications to global tests. Ann. Statist. 41, 296–322.

    Google Scholar 

  23. V. Petrov (1995). Limit Theorems of Probability Theory: Sequences of Independent Random Variables. Oxford University Press, London.

    Google Scholar 

  24. C. Stein (1972). A bound for error in the normal approximation to the distribution of a sum of dependent random variables. Proc. Sixth Berkeley Symp. Math. Stat. Probab. 2, 586–602. Berkeley: University of California Press.

    Google Scholar 

  25. T.J. Sweeting (1977). Speeds of convergence for the multidimensional central limit theorem. Ann. Probab. 5, 28–41.

    Google Scholar 

  26. T.J. Sweeting (1980). Speeds of convergence and asymptotic expansions in the central limit theorem: a treatment by operators. Ann. Probab. 8, 281–297.

    Google Scholar 

  27. A. Yu. Zaïtsev (1987). On the Gaussian approximation of convolutions under multidimensional analogues of S.N. Bernstein’s inequality conditions, Probability Theory and Related Fields 74, 535–566.

    Google Scholar 

Download references

Acknowledgements

The author would like to thank Xiao Fang, Weidong Liu, and Wenxin Zhou for their help in preparing this note. Partially supported by Hong Kong RGC - GRF 403513.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Qi-Man Shao .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Shao, QM. (2016). An Introduction to Normal Approximation. In: Denker, M., Waymire, E. (eds) Rabi N. Bhattacharya. Contemporary Mathematicians. Birkhäuser, Cham. https://doi.org/10.1007/978-3-319-30190-7_3

Download citation

Publish with us

Policies and ethics