Skip to main content
Log in

Von mises approximation of the critical value of a test

  • Published:
Test Aims and scope Submit manuscript

Abstract

In this paper we propose a von Mises approximation of the critical value of a test and a saddlepoint approximation of it. They are specially useful to compute quantiles of complicated test statistics with a complicated distribution function, which is a very common situation in robustness studies. We also obtain the influence function of the critical value as an alternative way to analyse the robustness of a test.

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

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Daniels, H. E. (1983). Saddlepoint approximations for estimating equations.Biometrika, 70:89–96.

    Article  MATH  MathSciNet  Google Scholar 

  • Fernholz, L. T. (1983).von Mises Calculus for Statistical Functionals, vol. 19 ofLecture Notes in Statistics. Springer-Verlag, New York.

    Google Scholar 

  • Fernholz, L. T. (2001). On multivariate higher order von Mises expansions.Metrika, 53:123–140.

    Article  MATH  MathSciNet  Google Scholar 

  • Field, C. A. andRonchetti, E. (1985). A tail area influence function and its application to testing.Communications in Statistics, 4:19–41.

    MATH  MathSciNet  Google Scholar 

  • Field, C. A. andRonchetti, E. (1990).Small Sample Asymptotics, vol. 13 ofLecture Notes-Monograph Series. Institute of Mathematical Statistics, Hayward, California.

    Google Scholar 

  • Filippova, A. A. (1961). Mises' theorem on the asymptotic behaviour of functionals of empirical distribution functions and its statistical applications.Theory of Probability and its Applications, 7:24–57.

    Article  Google Scholar 

  • García-Pérez, A. (1993). On robustness for hypotheses testing.International Statistical Review, 61:369–385.

    Article  Google Scholar 

  • García-Pérez, A. (1996). Behaviour of sign test and one sample median test against changes in the model.Kybernetika, 32:159–173.

    MATH  MathSciNet  Google Scholar 

  • García-Pérez, A. (2000). An alternative way to accept a family of distributions for the observable random variable. InProceedings of the International Workshop GOF2000 on Goodness-of-fit Tests and Validity of Models, pp. 67–68. University of Paris V, Paris.

    Google Scholar 

  • Gatto, R. andRonchetti, E. (1996). General saddlepoint approximation of marginal densities and tail probabilities.Journal of the American Statistical Association, 91:666–673.

    Article  MATH  MathSciNet  Google Scholar 

  • Hampel, F. R. (1968).Contributions to the Theory of Robust Estimation. Ph.D. thesis, University of California, Berkeley.

    Google Scholar 

  • Hampel, F. R. (1974). The influence curve and its role in robust estimation.Journal of the American Statistical Association, 69:383–393.

    Article  MATH  MathSciNet  Google Scholar 

  • Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., andStahel, W. A. (1986).Robust Statistics: The Approach Based on Influence Functions. Wiley, New York.

    MATH  Google Scholar 

  • Jensen, J. L. (1995).Saddlepoint Approximations, vol. 16 ofOxford Statistical Science Series. The Clarendon Press Oxford University Press, New York. Oxford Science Publications.

  • Loh, W.-Y. (1984). Bounds on AREs for restricted classes of distributions defined via tail-orderings.The Annals of Statistics, 12:685–701.

    MATH  MathSciNet  Google Scholar 

  • Lugannani, R. andRice, S. (1980). Saddle point approximation for the distribution of the sum of independent random variables.Advances in Applied Probability, 12:475–490.

    Article  MATH  MathSciNet  Google Scholar 

  • Maesono, Y. andPenev, S. I. (1998). Higher order relations between Cornish-Fisher expansions and inversions of saddlepoint approximations.Journal of the Japan Statistical Society, 28:21–38.

    MATH  MathSciNet  Google Scholar 

  • Reeds, J. A. (1976).On the Definitions of von Mises Functionals. Ph.D. thesis, Harvard University, Cambridge, Massachusetts.

    Google Scholar 

  • Rousseeuw, P. J. andRonchetti, E. (1979). The influence curve for tests. Tech report, Fachgruppe fur Statistik ETH, Zurich.

    Google Scholar 

  • Rousseeuw, P. J. andRonchetti, E. (1981). Influence curves for general statistics.Journal of Computational and Applied Mathematics, 7:161–166.

    Article  MATH  MathSciNet  Google Scholar 

  • Sen, P. K. (1988). Functional jackknifing: Rationality and general asymptotics.The Annals of Statistics, 16:450–469.

    MATH  MathSciNet  Google Scholar 

  • Serfling, R. J. (1980).Approximation Theorems of Mathematical Statistics. Wiley, New York.

    MATH  Google Scholar 

  • von Mises, R. (1947). On the asymptotic distribution of differentiable statistical functions.The Annals of Mathematical Statistics, 18:309–348.

    MATH  Google Scholar 

  • Whithers, C. S. (1983). Expansions for the distribution and quantiles of a regular functional of the empirical distribution with applications to nonparametric confidence intervals.The Annals of Statistics, 11:577–587.

    MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alfonso García-Pérez.

Rights and permissions

Reprints and permissions

About this article

Cite this article

García-Pérez, A. Von mises approximation of the critical value of a test. Test 12, 385–411 (2003). https://doi.org/10.1007/BF02595721

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02595721

Key Words

AMS subject classification

Navigation