Abstract
Comparing the sample mean to the sample median gives rise to a test of univariate symmetry commonly referred to as the MM-test of symmetry. The general idea underlying this test is that the mean and median are equal at symmetric distributions, but not necessarily so at asymmetric distributions. In this paper, we study properties of a more general form of the MM-test of symmetry based upon the comparison of any two location estimators, and in particular upon the comparison of two different M-estimators of location. For these generalized MM-tests of symmetry, the asymptotic null distribution is obtained as well as the asymptotic distribution under local alternatives to symmetry. The local power functions help provide guidelines for choosing good members within the class of MM-tests of symmetry, e.g. in choosing good tuning constants for the M-estimators of location. A study of the local power also shows the advantages of the MM-test relative to other tests of symmetry. The results of the paper are shown to readily extend to testing the symmetry of the error term in a linear model.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Azzalini, A.: A class of distributions which includes the normal ones. Scand. J. Stat. 12, 171–178 (1985)
Bickel, P.J.: One-step Huber estimates in the linear model, J. Am. Stat. Assoc. 70, 428–434 (1975)
Bowley, A.L.: Elements of Statistics, (4th edn., 1920). Scribner’s, New York (1901)
Cassart, D., Hallin, M., Paindaveine, D.: Optimal detection of Fechner asymmetry. J. Stat. Plan. Infer. 138, 2499–2525 (2008)
Charlier, C.V.L.: Über das Fehlergesetz. Ark. Mat. Astron. Fys. 2, 1–9 (1905)
David, F.N., Johnson, N.L.: Statistical treatment of censored data: part I. fundamental formulae. Biometrika 41, 228–240 (1954)
Edgeworth, F.Y.:, The law of error. Trans. Camb. Philos. Soc. 20, 36–65, 113–141 (1904)
Eubank, R.L., LaRiccia, V.N., Rosenstein, R.B.: Test statistics derived as components of pearson’s Phi-Squared distance measure. J. Am. Stat. Assoc. 82, 816–825 (1987)
Eubank, R.L., LaRiccia, V.N., Rosenstein, R.B.: Testing symmetry about an unknown median, via linear rank procedures. J. Nonparametr. Stat. 1, 301–311 (1992)
Fechner, G.T.: Kollectivmasslehre. Engleman, Leipzig (1897)
Genton, M.G. (ed.): Skew-Elliptical Distributions and their Applications: A Journey Beyond Normality. Chapman and Hall/CRC, Boca Raton (2004)
Gupta, M.K.: An asymptotically nonparametric test of symmetry. Ann. Math. Stat. 38, 849–866 (1967)
Hájek, J., Šidák, Z.: Theory of Rank Tests. Academic Press, New York (1967)
Hettmansperger, T.P., McKean, J.W., Sheather, S.J.: Finite sample performance of tests for symmetry of the errors in a linear model. J. Stat. Comput. Simul. 72, 863–879 (2002)
Hettmansperger, T.P., McKean, J.W., Sheather, S.J.: Testing symmetry of the errors of a linear model. In: Moore, M., Froda, S., Léger, C. (eds.) Mathematical Statistics and Applications: Festschrift for Constance van Eeden. Lecture Notes - Monograph Series, pp. 99–112. Institute of Mathematical Statistics (2003)
Huber, P.J.: Robust estimation of a location parameter, Ann. Math. Stat. 35, 73–101 (1964)
Huber, P.J., Ronchetti, E.M.: Robust Statistics, 2nd edn. Wiley, New York (2009)
Kankainen, A., Taskinen, S. Oja, H.: Tests of multinormality based on location vectors and scatter matrices, Stat. Methods Appl. 16, 357–379 (2007)
Lopuhaä, H.P: Asymptotics of reweighted estimators of multivariate location and scatter. Ann. Stat. 27, 1638–1665 (1999)
Maronna, R.A., Martin, R.D., Yohai, V.J.: Robust Statistics: Theory and Methods. Wiley, Chichester (2006)
Pearson, K.: Contributions to the mathematical theory of evolution II. Skew variation in homogeneous material. Philos. Trans. R. Soci. Lond. A 186, 343–414 (1895)
Wang, J., Tyler, D.E.: A graphical method for detecting asymmetry. In: Transactions of the 63rd Deming Conference, Dec 2007
Wang, J.: Some properties of robust statistics under asymmetric models. Ph.D. Dissertation, Department of Statistics, Rutgers–The State University of New Jersey (2008)
Yule, G.U.: Introduction to the Theory of Statistics. Griffin, London (1911)
Acknowledgements
David Tyler’s research was supported in part by National Science Foundation Grant DMS-1407751. The authors are extremely grateful to the reviewers for their many helpful comments. In particular, Remark 8.1 was motivated by one of their insightful comments.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Wang, J., Tyler, D.E. (2015). Generalized MM-Tests for Symmetry. In: Nordhausen, K., Taskinen, S. (eds) Modern Nonparametric, Robust and Multivariate Methods. Springer, Cham. https://doi.org/10.1007/978-3-319-22404-6_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-22404-6_8
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-22403-9
Online ISBN: 978-3-319-22404-6
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)