Robust model selection with flexible trimming

Computational Statistics and Data Analysis

Volumn 54, Issue 12, 2010, Pages 3300-3312

  Riani, Marco ^a   Atkinson, Anthony C ^b  

^a UNIVERSITY OF PARMA   (Italy)

^b LONDON SCHOOL OF ECONOMICS   (United Kingdom)

Author keywords

Candlestick plot; Distributional robustness; F distribution; Forward search; M estimation

Indexed keywords

REGRESSION ANALYSIS; STATISTICAL TESTS; TRIMMING;

CANDLESTICK PLOT; DISTRIBUTIONAL ROBUSTNESS; F DISTRIBUTION; FORWARD SEARCH; M-ESTIMATION;

IMAGE ENHANCEMENT;

EID: 77955387008     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2010.03.007     Document Type: Article

References (35)

1. Agostinelli, C., 2002. Robust model selection in regression via weighted likelihood methodology. Statistics and Probability Letters 56, 289-300.
2. Akaike, H., 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716-723.
3. Atkinson, A.C., 1985. Plots, Transformations, and Regression. Oxford University Press, Oxford.
4. Atkinson, A.C., Riani, M., 2000. Robust Diagnostic Regression Analysis. Springer-Verlag, New York.
5. Atkinson, A.C., Riani, M., 2002. Forward search added variable t tests and the effect of masked outliers on model selection. Biometrika 89, 939-946. (Pubitemid 41311956)
6. Atkinson, A.C., Riani, M., 2007. Building regression models with the forward search. Journal of Computing and Information Technology-CIT 15, 287-294. doi:10.2489/cit.1001135.
7. Atkinson, A.C., Riani, M., 2008. A robust and diagnostic information criterion for selecting regression models. Journal of the Japanese Statistical Society 38, 3-14.
8. Box, G.E.P., Watson, G.S., 1962. Robustness to non-normality of regression tests. Biometrika 49, 93-106.
9. Breiman, L, Friedman, J.H., 1985. Estimating optimal transformations for multiple regression and transformation (with discussion). Journal of the American Statistical Association 80, 580-619.
10. Cantoni, E., Ronchetti, E., 2001. Robust inference for generalized linear models. Journal of the American Statistical Association 96, 1022-1030.
11. Cook, S., Weisberg, 1982. Residuals and Influence in Regression. Chapman and Hall, London.
12. p-statistic. The Statistician 45, 49-56.
13. Green, P.J., 1995. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82, 711-732.
14. Hurvich, C.M., Tsai, C.-L., 1989. Regression and time series model selection in small samples. Biometrika 76, 297-307.
15. Khan, J., Van Aelst, S., Zamar, R., 2007a. Building a robust linear model with forward selection and stepwise procedures. Computational Statistics and Data Analysis 52, 239-248. (Pubitemid 47331718)
16. Khan, J., Van Aelst, S., Zamar, R., 2007b. Robust linear model selection based on least angle regression. Journal of the American Statistical Association 102, 1289-1299.
17. Lutz, R., Kalisch, M., Bühlmann, P., 2008. Robustified L2 boosting. Computational Statistics and Data Analysis 52, 3331-3341.
18. p. Technometrics 15, 661-675.
19. Maronna, R.A., Martin, D.R., Yohai, V.J., 2006. Robust Statistics: Theory and Methods. Wiley, New York.
20. McCann, L, Welsch, R.E., 2007. Robust variable selection using least angle regression and elemental set sampling. Computational Statistics and Data Analysis 52, 249-257.
21. Morgenthaler, S., Welsch, R., Zenide, A., 2003. Algorithms for robust model selection in linear regression. In: Hubert, M., Pison, G., Struyf, A., Van Aelst, S. (Eds.), Theory and Applications of Recent Robust Methods. Birkhäuser-Verlag, Basel, pp. 101-109.
22. Müller, S., Welsh, A.H., 2005. Outlier robust model selection in linear regression. Journal of the American Statistical Association 100, 1297-1310. (Pubitemid 41801277)
23. Prentice, R.L., 1974. Degrees-of-freedom modifications for F tests based on nonnormal errors. Biometrika 61, 559-563.
24. Qjan, G., Künsch, H.R., 1998. On model selection via stochastic complexity in robust linear regression. Journal of Statistical Planning and Inference 75, 91-116.
25. Riani, M., Atkinson, A.C., 2007. Fast calibrations of the forward search for testing multiple outliers in regression. Advances in Data Analysis and Classification 1, 123-141. doi:10.1007/s11634-007-0007-y. (Pubitemid 47216145)
26. Riani, M., Atkinson, A.C., 2010. The selection of time series models perhaps with regressors (submitted for publication).
27. Riani, M., Atkinson, A.C., Cerioli, A., 2009. Finding an unknown number of multivariate outliers. Journal of the Royal Statistical Society, Series B 71, 447-466.
28. Ronchetti, E., 1997. Robustness aspects of model choice. Statistica Sinica 7, 327-338.
29. Ronchetti, E., Field, C., Blanchard, W., 1997. Robust linear model selection by cross-validation. Journal of the American Statistical Association 92, 1017-1023.
30. p. Journal of the American Statistical Association 89, 550-559.
31. Rousseeuw, P.J., 1984. Least median of squares regression. Journal of the American Statistical Association 79, 871-880.
32. Salibian-Barrera, M., Van Aelst, S., 2008. Robust model selection using fast and robust bootstrap. Computational Statistics and Data Analysis 52, 5121-5135.
33. p. Journal of the Royal Statistical Society Series C (Applied Statistics) 45, 15-29.
34. Tallis, G.M., 1963. Elliptical and radial truncation in normal samples. Annals of Mathematical Statistics 34, 940-944.
35. Tong, H., 2001. A personal journey through time series in Biometrika. Biometrika 88, 195-218. (Pubitemid 33771344)