Longitudinal data analysis using t-type regression

Journal of Statistical Planning and Inference

Volumn 122, Issue 1-2, 2004, Pages 253-269

  He, Xuming ^a   Cui, Hengjian ^b   Simpson, Douglas G ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^b BEIJING NORMAL UNIVERSITY   (China)

Author keywords

Asymptotic normality; Correlation; Longitudinal data; M estimator; One step estimator; t type regression

Indexed keywords

EID: 1542288392     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jspi.2003.06.002     Document Type: Article

References (20)

1. Barclay M. Bid-Ask spreads and the avoidance of odd-eighth quotes on NASDAQ: an examination of exchange listings J. Financial Economics 45 1997 35-38
2. Davies P.L. Asymptotic behavior of S-estimates of multivariate location parameters and dispersion matrices Ann. Statist. 15 1987 1269-1292
3. Dempster A.P. Laird N.M. Rubin D.B. Maximum likelihood from incomplete data via the EM algorithm (with Discussion) J. R. Statist. Soc. B 39 1977 1-38
4. Godambe V.P. Estimating Functions 1991 Clarendon Press Oxford
5. Hampel F.R. Ronchetti E.M. Rousseeuw R.J. Stahel W.A. Robust Statistics 1986 Wiley New York
6. He X. A local breakdown property of robust tests in linear regression J. Multiva. Anal. 38 1991 294-305
7. He X. Wang G. Cross-checking using the minimum volume ellipsoid estimator Stat. Sinica 6 1996 367-374
8. He X. Shao Q.M. A general Bahadur representation of M-estimators and its application to linear regression with nonstochastic designs Ann. Statist. 24 1996 2608-2630
9. He X. Simpson D.G. Wang G.Y. Breakdown points of t-type regression estimators Biometrika 87 2000 675-687
10. Huang R.D. Stoll H.R. Dealer versus auction markets: a paired comparison of execution costs on NASDAQ and the NYSE J. Finance Econ. 41 1996 313-357
11. Huber, P.J., 1967. The behavior of maximum likelihood estimates under nonstandard conditions. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, pp. 221-233.
12. Lange K.L. Little R.J.A. Taylor J.M.G. Robust statistical modeling using the t distribution J. Amer. Statist. Assoc. 84 1989 881-896
13. Liang K.-Y. Zeger S.L. Longitudinal data analysis using generalized linear models Biometrika 73 1986 13-22
14. Little R.J.A. Robust estimation of the mean and covariance matrix from data with missing values Applied Statistics 37 1988 23-28
15. Markatou M. Mixture models, robustness, and the weighted likelihood methodology Biometrics 56 2 2000 483-486
16. Maronna R.A. Yohai V.J. Asymptotic behavior of general M-estimates for regression and scale with random carries Z. Wahr. Ver. Geb. 58 1981 7-21
17. Pollard, D., 1990. Empirical processes: theory and applications. NSF-CBMS Regional Conference Series in Probability and Statistics, Vol. 2. Institute of Mathematical Statistics, Hayward, California.
18. Rousseeuw, P.J., Yohai, V., 1984. Robust regression by means of S-estimators. In: Franke, J., Hardle, W., Martin, R.D. (Eds.), Robust and Nonlinear Time Series Analysis. Springer, Berlin and New York, pp. 256-272.
19. Simpson D.G. Yohai V.J. Functional stability of one-step GM-estimators in approximately linear regression Ann. Statist. 26 1998 1147-1169
20. Simpson D.G. Ruppert D. Carroll R.J. On one-step GM estimates and stability of inferences in linear regression J. Am. Stat. Assoc. 87 1992 439-450