Matías Salibián-Barrera [Publications]



  • Azadeh, A. and Salibian-Barrera, M. (2009). An outlier-robust fit for Generalised Additive Models with applications to outbreak detection. Submitted. Available here. R code is available here.

  • Tharmaratnam, K., Claeskens, G., Croux, C. and Salibian-Barrera, M. (2009). S-estimation for penalised regression splines. Submitted. Available here. R code is available here.

  • Adrover, J. and Salibian-Barrera, M. (2009). Globally robust confidence intervals for simple linear regression. To appear in Computational Statistics and Data Analysis. The latest manuscript is available here. A first version of the accepted paper is available here.

  • Salibian-Barrera, M. and Wei, Y. (2008). Weighted quantile regression with non-elliptically structured covariates. The Canadian Journal of Statistics, 36, 595-611.

  • Salibian-Barrera, M. and Van Aelst, S. (2008). Robust model selection using fast and robust bootstrap. Computational Statistics and Data Analysis, 52, 5121-5135. DOI link here.

  • Omelka, M. and Salibian-Barrera, M. (2008). Uniform asymptotics for S- and MM-regression estimators. To appear in the Annals of the Institute of Statistical Mathematics. A technical report is available here. A first version is available on-line here.

  • Harrington, J. and Salibian-Barrera, M. (2008). Finding approximate solutions to combinatorial problems with very large data sets using BIRCH. To appear in appear in Computational Statistics and Data Analysis. A first version is available on-line here.

  • Salibian-Barrera, M. and Yohai, V.J. (2008). High breakdown point robust regression with censored data. The Annals of Statistics, 36, 118-146. Available here and here. A related technical report is available here.

  • Salibian-Barrera, M., Willems, G. and Zamar, R.H. (2008). The fast-tau estimator for regression. Journal of Computational and Graphical Statistics, 17, 659-682. Available here. An earlier version of the same paper, titled “Computation of tau-estimates for linear regresion”, is available here. MATLAB & OCTAVE code for this algorithm is available here.

  • Salibian-Barrera, M. and Yohai, V.J. (2006). A fast algorithm for S-regression estimates. Journal of Computational and Graphical Statistics 15, 414-427. Available here. R code for this algorithm is available here.

  • Salibian-Barrera, M. (2006). The asymptotics of MM-estimators for linear regression with fixed designs. Metrika, 63, 283-294. The paper is available on-line here.

  • Salibian-Barrera, M., Van Aels, S. and Willems, G. (2007). Fast and robust bootstrap. Statistical Methods and Applications. Available on-line here.

  • Farrell, P.J. and Salibian-Barrera, M. (2006). A comparison of several robust estimators for a finite population mean. Invited paper to appear in a special issue of the Journal of Statistical Studies on the occasion of Prof. A. K. Md. Ehsanes Saleh's 75th birthday. A preliminary (PDF) version is here.

  • Salibian-Barrera, M. and Zamar, R.H. (2006). Discussion on "Conditional growth charts" by Wei, Y. and He, X. The Annals of Statistics, 34, 2113-2118.

  • Salibian-Barrera, M. (2006). Bootstrapping MM-estimators for linear regression with fixed designs. Statistics and Probability Letters, 76, 1287-1297.

  • Salibian-Barrera, M., Van Aelst, S. and Willems, G. (2006). PCA based on multivariate MM-estimators with fast and robust bootstrap. Journal of the American Statistical Association, 101, 1198-1211.

  • Farrell, P.J., Salibian-Barrera, M. and Naczk, K. (2006). On tests for multivariate normality and associated simulation studies. To appear in the Journal of Statistical Computation and Simulation. A preprint is available here as PDF and PS.

  • Salibian-Barrera, M. (2005). Estimating the p-values of robust tests for the linear model. Journal of Statistical Planning and Inference, 128, 241-257.

  • Salibian-Barrera, M. (2005). Recent advances in globally robust inference methods. Journal of Statistical Research, 39, 139-156.

  • Adrover, J.G, Salibian-Barrera, M. and Zamar, R.H. (2004). Globally robust inference for the location and simple linear regression models. Journal of Statistical Planning and Inference, 119, 353-375.

  • Salibian-Barrera, M. and Zamar, R.H. (2004). Uniform asymptotics for robust location estimates when the scale is unknown. The Annals of Statistics, 32, 1434-1447.

  • Salibian-Barrera, M. (2003). Fast and stable bootstrap methods for robust estimates. Computing Science and Statistics, 34, 346-359 (E. Wegman and A. Braverman editors). Interface Foundation of North America, Inc., Fairfax Station, VA.

  • Salibian-Barrera, M. and Zamar, R.H. (2002). Bootstrapping robust estimates of regression. The Annals of Statistics, 30, 556-582.

  • Adrover, J., Berrendero, J.R., Salibian-Barrera, M. and Zamar, R.H. (2002). Globally Robust Inference (a review). Estadistica. Available in PDF format.

  • Maronna, R. A., Salibian-Barrera, M. and Yohai, V. J. (2000). Improving bias-robustness of regression estimates through projections. Statistics and Probability Letters. 47, 149-158

  • Salibian-Barrera, M. (2000). Contributions to the theory of robust inference. PhD Thesis. Department of Statistics, University of British Columbia. Available in Postscript and PDF formats.

  • Salibian-Barrera, M. (1998). On Globally Robust Confidence Intervals for Regression Coefficients, UBC Department of Statistics Technical Report #176. Available as postscript or as HTML.






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