References

  1. Abraham, B. and Chuang, A. (1989), Expectation–maximization algorithms and the estimation of time series models in the presence of outliers, Journal of Time Series Analysis, 14, 221–234.
  2. Adrover, J. and Yohai, V.J. (2002), Projection estimates of multivariate location. The Annals of Statistics, 30, 1760–1781.
  3. Adrover, J., Maronna, R.A. and Yohai, V.J. (2002), Relationships between maximum depth and projection regression estimates, Journal of Statistical Planning and Inference, 105, 363–375.
  4. Agostinelli, C. and Yohai, V.J. (2016), Composite robust estimators for linear mixed models. Journal of American Statistical Association, 111, 1764–1774.
  5. Agostinelli, C., Leung, A., Yohai, V.J. and Zamar, V.J. (2015), Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination. Test, 24, 441–461.
  6. Agulló, J. (1996), Exact iterative computation of the multivariate minimum volume ellipsoid estimator with a branch and bound algorithm, Proceedings of the 12th Symposium in Computational Statistics (COMPSTAT 12), 175–180.
  7. Agulló, J. (1997), Exact algorithms to compute the least median of squares estimate in multiple linear regression, in Y. Dodge (ed.), L1‐Statistical Procedures and Related Topics, Institute of Mathematical Statistics Lecture Notes – Monograph Series, vol. 31, pp. 133–146.
  8. Agulló, J. (2001), New algorithms for computing the least trimmed squares regression estimator, Computational Statistics and Data Analysis, 36, ...

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