Matías Salibián-Barrera [Publications]



  • Kondo, Y., Salibian-Barrera, M. and Zamar, R. H. (2012) A robust and sparse K-means clustering algorithm. A preprint is available at arXiv:1201.6082v1.
    The corresponding R package (RSKC) is available from CRAN (a direct link is here).
    This work is based on Yumi's MSc thesis (available here).

  • Azadeh, A. and Salibian-Barrera, M. (2011). An outlier-robust fit for Generalized Additive Models with applications to disease outbreak detection. To appear in the Journal of the American Statistical Association. Available on-line here and here. A preliminary manuscript is also available here.
    The corresponding R package is available here.

  • Tharmaratnam, K., Claeskens, G., Croux, C. and Salibian-Barrera, M. (2010). S-estimation for penalised regression splines. Journal of Computational and Graphical Statistics, 19(3), 609-625.
    Available on-line     here.
    R code implementing the method is available here.

  • Adrover, J. and Salibian-Barrera, M. (2010). Globally robust confidence intervals for simple linear regression. Computational Statistics and Data Analysis, 54(12), 2899-2913.
    Available on-line     here.
    R code implementing the method is available here.

  • Omelka, M. and Salibian-Barrera, M. (2010). Uniform asymptotics for S- and MM-regression estimators. Annals of the Institute of Statistical Mathematics, 62(5), 897-927.
    A technical report is available     here.
    Available on-line here.

  • Harrington, J. and Salibian-Barrera, M. (2010). Finding approximate solutions to combinatorial problems with very large data sets using BIRCH. Computational Statistics and Data Analysis, 54, 655-667.
    Available on-line here.
    R code implementing the method 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.
    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 on-line 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. (2008). Fast and robust bootstrap. Statistical Methods and Applications 17, 41-71.
    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 for a volumen on the occasion of Prof. A. K. Md. Ehsanes Saleh's 75th birthday. Journal of Statistical Studies 26, 29-43.
    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.
    Available on-line here.

  • 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.
    Available on-line here.

  • Farrell, P.J., Salibian-Barrera, M. and Naczk, K. (2007). On tests for multivariate normality and associated simulation studies. Journal of Statistical Computation and Simulation, 77, 1065-1080.
    A preprint is available here.
    The paper is available on-line here.

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

  • 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.
    Available on-line here

  • 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.
    Available on-line here.

  • 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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