Skip to main content
Log in

Strong convergence rate of the least median absolute estimator in linear regression models

  • Articles
  • Published:
Statistical Papers Aims and scope Submit manuscript

Abstract

We propose a least median of absolute (LMA) estimator for a linear regression model, based on minimizing the median absolute deviation of the residuals. Under some regularity conditions on the design points and disturbances, the strong convergence rate of the LMA estimator is established.

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

  1. Croux, C; Hössjer, O. and Rousseeuw, P. J. (1994). Generalized S- estimators. J. Amer. Statist. Assoc. 89, 1271–1281.

    Article  MATH  MathSciNet  Google Scholar 

  2. Davies, P. L. (1987). Asymptotic behavior of S-estimates of multivariate location parameters and dispersion matrices. Ann. Statist. 15, 1269–1292.

    Article  MATH  MathSciNet  Google Scholar 

  3. Davies, P. (1990). The asymptotic of S-estimators in the linear regression model. Ann. Statist 18, 1651–1675.

    Article  MATH  MathSciNet  Google Scholar 

  4. Hampel, F. M. (1975). The influence curve and its role in robust estimation. J. Amer. Statist. Math. 69, 383–397.

    MathSciNet  Google Scholar 

  5. Hampel, F. M.; Ronchetti, E. M.; Rousseeuw, P. J. and Stahel, W. A. (1986). Robust Statistics: The Approach Based on Influence function. Wiley, New York.

    MATH  Google Scholar 

  6. Hössjer, O. (1992). On the optimality of S-estimators. Statistics and Probability Letters 14, 413–419.

    Article  MATH  MathSciNet  Google Scholar 

  7. Hössjer, O.; Croux, C. and Rousseeuw, P. J. (1994). Asymptotic of generalized S-estimators. J. of Multivariate Analysis 51, 148–177.

    Article  MATH  Google Scholar 

  8. Huber, P. J. (1981). Robust Statistics. Wiley, New York.

    Book  MATH  Google Scholar 

  9. Kim, J. and Pollard, D. (1990). Cube root asymptotics. Ann. Statist. 18, 191–219.

    Article  MATH  MathSciNet  Google Scholar 

  10. Pollard, D. (1990). Empirical Processes Theory and Application. Conference Board of the Mathematical Sciences, Regional Conference Series in Probability and Statistics, Institute of Mathematical Statistics, Hayward, California.

    Google Scholar 

  11. Rousseeuw, P. J. (1984). Least median of squares regression. J. Amer. Statist. Assoc. 79, 871–880.

    Article  MATH  MathSciNet  Google Scholar 

  12. Rousseeuw, P. J. and Leroy, A. M. (1987). Robust Regression and Outlier Detection. Wiley, New York.

    Book  MATH  Google Scholar 

  13. Rousseeuw, P. J. and Yohai, V. (1984). Robust Regression by means of S-estimators. Robust and Nonlinear Time Series Analysis. Lecture Notes in Statist. 26, 256–272. Springer, New York.

    Google Scholar 

  14. Serfling, R. J. (1980). Approximation Theorems of Mathematical Statistics. John Wiley & Sons, New York.

    Book  MATH  Google Scholar 

  15. Stromberg, A. J. (1995). Consistency of the least median of squares estimator in nonlinear regression. Commun. Statist. —Theory Meth. 24, 1971–1984.

    Article  MATH  MathSciNet  Google Scholar 

  16. Stromberg, A. J. (1993). Computing the exact least median of squares estimate and stability diagnostics in multiple linear regression. SIAM J. of Scientific Computing. 14, 1289–1299.

    Article  MATH  Google Scholar 

  17. Theil, H. (1971). Principle of Econometrics. John Wiley & Sons, New York.

    Google Scholar 

  18. Uspensk, P. (1937). Introduction to Mathematical Probability. MeGraw-Hill, New York.

    Google Scholar 

  19. Yang, Y. and Wang, B. Z. (1999). Bahadur’s representation for nearest neighbor median estimates: the fixed design case. Systems Sci. & Math. Sci. 12, 133–144.

    MATH  MathSciNet  Google Scholar 

  20. Yang, Y. and Zheng, Z. G. (1997). Asymptotic properties for median crossvalidated nearest neighbor median estimate in nonparametric regression. Science in China (Series A) 40, 585–597.

    Article  MATH  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ip, W.C., Yang, Y., Kwan, P.Y.K. et al. Strong convergence rate of the least median absolute estimator in linear regression models. Statistical Papers 44, 183–201 (2003). https://doi.org/10.1007/s00362-003-0145-z

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00362-003-0145-z

Keywords

Running Title

Mathematics Subject Classification (2000)

Navigation