Skip to main content
Log in

The limit distribution of weighted \(L^2\)-goodness-of-fit statistics under fixed alternatives, with applications

  • Published:
Annals of the Institute of Statistical Mathematics Aims and scope Submit manuscript

Abstract

We present a general result on the limit distribution of weighted one- and two-sample \(L^2\)-goodness-of-fit test statistics of some hypothesis \(H_0\) under fixed alternatives. Applications include an approximation of the power function of such tests, asymptotic confidence intervals of the distance of an underlying distribution with respect to the distributions under \(H_0\), and an asymptotic equivalence test that is able to validate certain neighborhoods of \(H_0\).

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

Access this article

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

  • Alba-Fernández, V., Jiménez-Gamero, M. D. (2015). Testing for a class of bivariate exponential distributions. International Journal of Computer Mathematics, 92, 1733–1754.

  • Baringhaus, L., Franz, C. (2010). Rigid motion invariant two-sample tests. Statistica Sinica, 20, 1333–1361.

  • Baringhaus, L., Henze, N. (1988). An invariant consistent test for multivariate normality. Metrika, 13, 269–274.

  • Baringhaus, L., Henze, N. (1991). A class of consistent tests for exponentiality based on the empirical Laplace transform. Annals of the Institute of Statistical Mathematics, 43, 551–564.

  • Baringhaus, L., Henze, N. (1992). A goodness-of-fit test for the Poisson distribution based on the empirical generating function. Statistics & Probability Letters, 13, 269–274.

  • Baringhaus, L., Gürtler, N., Henze, N. (2000). Weighted integral test statistics and components of smooth tests of fit. Australian & New Zealand Journal of Statistics, 42, 179–192.

  • Baringhaus, L., Kolbe, D. (2015). Two-sample tests based on empirical Hankel transforms. Statistical Papers, 56, 597–617.

  • Bücher, A., Dette, H. (2010). Some comments on goodness-of-fit tests for the parametric form of the copula based on \(L^2\)-distances. Journal of Multivariate Analysis, 101, 749–763.

  • Chapman, D. G. (1958). A comparative study of several one-sided goodness-of-fit tests. Annals of Mathematical Statistics, 29, 655–674.

    Article  MathSciNet  MATH  Google Scholar 

  • Czado, C., Freitag, G., Munk, A. (2007). A nonparametric test for similarity of marginals - with applications to the assessment of bioequivalence. Journal of Statistical Planning and Inference, 137, 697–711.

  • Dette, H., Munk, A. (2003). Some methodological aspects of validation of models in nonparametric regression. Statistica Neerlandica, 57, 207–244.

  • De Wet, T., Randles, R. H. (1987). On the effect of substituting parameter estimators in limiting \(\chi ^2\)-, \(U\)- and \(V\)-statistics. The Annals of Statistics, 15, 398–412.

  • Dunford, N., Schwartz, J. (1988). Linear Operators. Wiley, New York: Part II. Spectral theory. Selfadjoint operators in Hilbert space.

  • Ebner, B., Henze, N., Meintanis, S. (2012). Goodness-of-fit tests for the gamma distribution based on the empirical Laplace transform. Communications in Statistics. Theory and Methods, 41, 1543–1556.

  • Epps, T. W., Pulley, L. B. (1983). A test for normality based on the empirical characteristic function. Biometrika, 70, 723–726.

  • Fermanian, J. D. (2009). Goodness-of-fit tests for copulas. Journal of Multivariate Analysis, 95, 119–152.

    Article  MathSciNet  MATH  Google Scholar 

  • Fragiadakis, K., Karlis, D., Meintanis, S. (2009). Tests of fit for normal inverse Gaussian distributions. Statistical Methodology, 6, 553–564.

  • Genest, Ch., Kojadinovic, I., Nešlehová, J., Yan, J. (2011). A goodness-of-fit test for bivariate extreme-value copulas. Bernoulli, 17, 253–275.

  • Gürtler, N. (2000). Asymptotic results on the BHEP tests for multivariate normality with fixed and variable smoothing parameter (in German). Doctoral dissertation, University of Karlsruhe.

  • Gürtler, N., Henze, N. (2000a). Goodness-of-fit tests for the Cauchy distribution based on the empirical characteristic function. Annals of the Institute of Statistical Mathematics, 52, 267–286.

  • Gürtler, N., Henze, N. (2000b). Recent and classical goodness-of-fit tests for the Poisson distribution. Journal of Statistical Planning and Inference, 90, 207–225.

  • Gupta, A. K., Henze, N., Klar, B. (2004). Testing for affine equivalence of elliptically symmetric distributions. Journal of Multivariate Analysis, 88, 222–242.

  • Henze, N. (1990). An approximation to the limit null distribution of the Epps-Pulley test statistic for normality. Metrika, 37, 7–18.

    Article  MathSciNet  MATH  Google Scholar 

  • Henze, N. (1993). A flexible class of omnibus tests for exponentiality. Communications in Statistics. Theory and Methods, 22, 115–133.

    Article  MathSciNet  MATH  Google Scholar 

  • Henze, N. (1997). Extreme smoothing and testing for multivariate normality. Statistics & Probability Letters, 35, 203–213.

    Article  MathSciNet  MATH  Google Scholar 

  • Henze, N. (2002). Invariant tests for multivariate normality: A critical review. Statistical Papers, 43, 467–506.

    Article  MathSciNet  MATH  Google Scholar 

  • Henze, N., Klar, B. (2002). Goodness-of-fit tests for the Inverse Gaussian distribution based on the empirical Laplace transform. Annals of the Institute of Statistical Mathematics, 54, 425–444.

  • Henze, N., Meintanis, S. (2002a). Tests of fit for exponentiality based on the empirical Laplace transform. Statistics, 36, 147–161.

  • Henze, N., Meintanis, S. (2002b). Goodness-of-fit tests based on a new characterization of the exponential distribution. Communications in Statistics. Theory and Methods, 31, 1479–1497.

  • Henze, N., Meintanis, S. (2005). Recent and classical tests for exponentiality: A partial review with comparisons. Metrika, 61, 29–45.

  • Henze, N., Meintanis, S. (2010). A characterization and a class of omnibus tests for the exponential distribution based on the empirical characteristic function. Journal of Mathematical Sciences, 167, 588–595.

  • Henze, N., Wagner, T. (1997). A new approach to the BHEP tests for multivariate normality. Journal of Multivariate Analysis, 62, 1–23.

  • Henze, N., Zirkler, B. (1990). A class of invariant consistent tests for multivariate normality. Communications in Statistics. Theory and Methods, 19, 3595–3617.

  • Henze, N., Klar, B., Meintanis, S. (2003). Invariant tests for symmetry about an unspecified point based on the empirical characteristic function. Journal of Multivariate Analysis, 87, 275–297.

  • Henze, N., Klar, B., Zhu, L. (2005). Checking the adequacy of the multivariate semiparametric location shift model. Journal of Multivariate Analysis, 93, 238–256.

  • Hušková, M., Meintanis, S. (2008). Tests for the multivariate \(k\)-sample problem based on the empirical characteristic function. Journal of Nonparametric Statistics, 20, 263–277.

  • Iliopoulos, G., Meintanis, S. (2003). Tests of fit for the Rayleigh distribution based on the empirical Laplace transform. Annals of the Institute of Statistical Mathematics, 55, 137–151.

  • Ledoux, M., Talagrand, M. (2011). Probability in Banach spaces. Isoperimetry and processes. Berlin: Springer.

  • Leucht, A. (2012). Characteristic function-based tests under weak dependence. Journal of Multivariate Analysis, 108, 67–89.

    Article  MathSciNet  MATH  Google Scholar 

  • Magnus, W., Oberhettinger, F., Soni, R. (1966). Formulas and Theorems for the special functions of mathematical physics. Berlin: Springer.

  • Meintanis, S. (2004a). A class of omnibus tests for the Laplace distribution based on the empirical characteristic function. Communications in Statistics. Theory and Methods, 33, 925–948.

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis, S. (2004b). Goodness-of-fit tests for the logistic distribution based on empirical transforms. Sankhyā, 66, 306–326.

    MathSciNet  MATH  Google Scholar 

  • Meintanis, S. (2005). Permutation tests for homogeneity based on the empirical characteristic function. Journal of Nonparametric Statistics, 17, 583–592.

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis, S. (2007). Test of fit for Marshall–Olkin distributions with applications. Journal of Statistical Planning and Inference, 137, 3954–3963.

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis, S. (2008a). Tests for generalized exponential laws based on the empirical Mellin transform. Journal of Statistical Computation and Simulation, 78, 1077–1085.

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis, S. (2008b). A powerful method of assessing the fit of the lognormal distribution. Communications in Statistics. Theory and Methods, 37, 1948–1958.

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis, S. (2010). Testing skew normality via the moment generating function. Mathematical Methods of Statistics, 19, 64–72.

    Article  MathSciNet  MATH  Google Scholar 

  • Meintanis, S., Tsionas, E. (2010). Testing for the generalized normal-Laplace distribution with applications. Computational Statistics & Data Analysis, 54, 3174–3180.

  • Naito, K. (1997). On the asymptotic normality of the \(L_2\)-distance class of statistics with estimated parameters. Journal of Nonparametric Statistics, 8, 199–214.

    Article  MathSciNet  MATH  Google Scholar 

  • Ngatchou-Wandji, J. (2009). Testing for symmetry in multivariate distributions. Statistical Methodology, 6, 230–250.

    Article  MathSciNet  MATH  Google Scholar 

  • Novoa-Muñoz, F. N., Jiménez-Gamero, M. D. (2014). Testing for the bivariate Poisson distribution. Metrika, 77, 771–793.

  • Rueda, R., Pérez-Abreu, V., O’ Reilly, F. (1991). Goodness of fit test for the Poisson distribution based on the probability generating function. Communications in Statistics. Theory and Methods, 20, 3093–3110.

  • Wellek, S. (2010). Testing statistical hypotheses of equivalence and noninferiority. Boca Raton: CRC Press.

    Book  MATH  Google Scholar 

Download references

Acknowledgments

The authors would like to thank Ya. Yu. Nikitin for drawing our attention to the paper of Chapman (1958) and B. Klar for pointing out the reference Naito (1997). Thanks go to two anonymous referees for their careful reading of the manuscript and for helpful suggestions.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to B. Ebner.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baringhaus, L., Ebner, B. & Henze, N. The limit distribution of weighted \(L^2\)-goodness-of-fit statistics under fixed alternatives, with applications. Ann Inst Stat Math 69, 969–995 (2017). https://doi.org/10.1007/s10463-016-0567-8

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10463-016-0567-8

Keywords

Navigation