R package 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 416 articles )

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  1. Fiorentini, Gabriele; Sentana, Enrique: New testing approaches for mean-variance predictability (2021)
  2. Güney, Yeşim; Tuaç, Y.; Özdemir, Ş.; Arslan, O.: Conditional maximum Lq-likelihood estimation for regression model with autoregressive error terms (2021)
  3. Hesamian, Gholamreza; Akbari, Mohammad Ghasem: A robust multiple regression model based on fuzzy random variables (2021)
  4. Poudyal, Chudamani: Truncated, censored, and actuarial payment-type moments for robust fitting of a single-parameter Pareto distribution (2021)
  5. Ramirez-Padron, Ruben; Mederos, Boris; Gonzalez, Avelino J.: Robust weighted Gaussian processes (2021)
  6. Agostinelli, Claudio; Bianco, Ana M.; Boente, Graciela: Robust estimation in single-index models when the errors have a unimodal density with unknown nuisance parameter (2020)
  7. Babos, Stephen; Artemiou, Andreas: Sliced inverse median difference regression (2020)
  8. Bagdonavičius, Vilijandas; Petkevičius, Linas: A new multiple outliers identification method in linear regression (2020)
  9. Beyhum, Jad: Inference robust to outliers with (\ell_1)-norm penalization (2020)
  10. Bianco, Ana M.; Boente, Graciela; Rodrigues, Isabel M.: Robust Wald-type methods for testing equality between two populations regression parameters: a comparative study under the logistic model (2020)
  11. Boente, Graciela; Rodriguez, Daniela; Vena, Pablo: Robust estimators in a generalized partly linear regression model under monotony constraints (2020)
  12. Boudt, Kris; Rousseeuw, Peter J.; Vanduffel, Steven; Verdonck, Tim: The minimum regularized covariance determinant estimator (2020)
  13. Chakraborty, Arnab; Lahiri, Soumendra Nath; Wilson, Alyson: A statistical analysis of noisy crowdsourced weather data (2020)
  14. Fauß, Michael; Zoubir, Abdelhak M.; Poor, H. Vincent: Minimax optimal sequential hypothesis tests for Markov processes (2020)
  15. Feng, Yunlong; Wu, Qiang: Learning under ((1 + \epsilon))-moment conditions (2020)
  16. Filzmoser, Peter; Gregorich, Mariella: Multivariate outlier detection in applied data analysis: global, local, compositional and cellwise outliers (2020)
  17. Filzmoser, P.; Höppner, S.; Ortner, I.; Serneels, S.; Verdonck, T.: Cellwise robust M regression (2020)
  18. Gerstenberger, Carina; Vogel, Daniel; Wendler, Martin: Tests for scale changes based on pairwise differences (2020)
  19. Hesamian, Gholamreza; Akbari, Mohammad Ghasem: A robust varying coefficient approach to fuzzy multiple regression model (2020)
  20. Laurent, Sébastien; Shi, Shuping: Volatility estimation and jump detection for drift-diffusion processes (2020)

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