robustbase

robustbase: Basic Robust Statistics ”Essential” Robust Statistics. The goal is to provide tools allowing to analyze data with robust methods. This includes regression methodology including model selections and multivariate statistics where we strive to cover the book ”Robust Statistics, Theory and Methods” by Maronna, Martin and Yohai; Wiley 2006.


References in zbMATH (referenced in 243 articles )

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  1. Alih, Ekele; Ong, Hong Choon: Robust cluster-based multivariate outlier diagnostics and parameter estimation in regression analysis (2017)
  2. Bergström, Per; Edlund, Ove: Robust registration of surfaces using a refined iterative closest point algorithm with a trust region approach (2017)
  3. Boente, Graciela; Vahnovan, Alejandra: Robust estimators in semi-functional partial linear regression models (2017)
  4. Bun, Joël; Bouchaud, Jean-Philippe; Potters, Marc: Cleaning large correlation matrices: tools from random matrix theory (2017)
  5. Callegaro, Giorgia; Gaïgi, M’hamed; Scotti, Simone; Sgarra, Carlo: Optimal investment in markets with over and under-reaction to information (2017)
  6. Cardot, Hervé; Godichon-Baggioni, Antoine: Fast estimation of the median covariation matrix with application to online robust principal components analysis (2017)
  7. Chachi, Jalal; Roozbeh, Mahdi: A fuzzy robust regression approach applied to bedload transport data (2017)
  8. Koller, Manuel; Stahel, Werner A.: Nonsingular subsampling for regression S estimators with categorical predictors (2017)
  9. Leão, Jeremias; Leiva, Víctor; Saulo, Helton; Tomazella, Vera: Birnbaum-Saunders frailty regression models: diagnostics and application to medical data (2017)
  10. O’Keefe, Christine M.; Ayre, Tim; Lucie, Sebastien; Khan, Atikur R.; Song, Soomin; Kwon, Soonmin: Perturbed robust linear estimating equations for confidentiality protection in remote analysis (2017)
  11. Atkinson, Anthony C.; Corbellini, Aldo; Riani, Marco: Introducing prior information into the forward search for regression (2016)
  12. Bako, Laurent; Ohlsson, Henrik: Analysis of a nonsmooth optimization approach to robust estimation (2016)
  13. Cavaliere, Giuseppe; Georgiev, Iliyan; Taylor, A.M.Robert: Sieve-based inference for infinite-variance linear processes (2016)
  14. Cerioli, Andrea; Atkinson, Anthony C.; Riani, Marco: How to marry robustness and applied statistics (2016)
  15. Chen, Ting-Li; Fujisawa, Hironori; Huang, Su-Yun; Hwang, Chii-Ruey: On the weak convergence and central limit theorem of blurring and nonblurring processes with application to robust location estimation (2016)
  16. Dürre, Alexander; Vogel, Daniel: Asymptotics of the two-stage spatial sign correlation (2016)
  17. Favre-Martinoz, Cyril; Haziza, David; Beaumont, Jean-François: Robust inference in two-phase sampling designs with application to unit nonresponse (2016)
  18. Ferraz do Nascimento, Fernando; Gamerman, Dani; Davis, Richard: A Bayesian semi-parametric approach to extreme regime identification (2016)
  19. García-Pérez, A.: A von Mises approximation to the small sample distribution of the trimmed mean (2016)
  20. Iannario, Maria; Monti, Anna Clara; Piccolo, Domenico: Robustness issues for cub models (2016)

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