R package quantreg: Quantile Regression. Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included. (Source: http://cran.r-project.org/web/packages)

References in zbMATH (referenced in 46 articles )

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  1. Boček, Pavel; Šiman, Miroslav: On weighted and locally polynomial directional quantile regression (2017)
  2. Chesher, Andrew: Understanding the effect of measurement error on quantile regressions (2017)
  3. Maistre, Samuel; Lavergne, Pascal; Patilea, Valentin: Powerful nonparametric checks for quantile regression (2017)
  4. Matthew Pietrosanu, Jueyu Gao, Linglong Kong, Bei Jiang, Di Niu: cqrReg: An R Package for Quantile and Composite Quantile Regression and Variable Selection (2017) arXiv
  5. Fuzi, Mohd Fadzli Mohd; Jemain, Abdul Aziz; Ismail, Noriszura: Bayesian quantile regression model for claim count data (2016)
  6. Galvao, Antonio F.; Kato, Kengo: Smoothed quantile regression for panel data (2016)
  7. Mingli Chen, Victor Chernozhukov, Ivan Fernandez-Val, Blaise Melly: Counterfactual: An R Package for Counterfactual Analysis (2016) arXiv
  8. Vincenzo Lagani, Giorgos Athineou, Alessio Farcomeni, Michail Tsagris, Ioannis Tsamardinos: Feature Selection with the R Package MXM: Discovering Statistically-Equivalent Feature Subsets (2016) arXiv
  9. Harrell, Frank E. jun.: Regression modeling strategies. With applications to linear models, logistic regression, and survival analysis (2015)
  10. Mak, T.K.; Nebebe, F.: A parametric approach for estimating conditional probability distributions (2015)
  11. Qoyyimi, Danang Teguh; Zitikis, Ricardas: Measuring association via lack of co-monotonicity: the loc index and a problem of educational assessment (2015)
  12. Valle, C.A.; Meade, N.; Beasley, J.E.: Factor neutral portfolios (2015)
  13. Kley, Tobias: Quantile-based spectral analysis: asymptotic theory and computation (2014)
  14. Nash, John C.: Nonlinear parameter optimization using R tools (2014)
  15. Peng, Limin; Xu, Jinfeng; Kutner, Nancy: Shrinkage estimation of varying covariate effects based on quantile regression (2014)
  16. Volgushev, Stanislav; Wagener, Jens; Dette, Holger: Censored quantile regression processes under dependence and penalization (2014)
  17. Alfons, Andreas; Croux, Christophe; Gelper, Sarah: Sparse least trimmed squares regression for analyzing high-dimensional large data sets (2013)
  18. Honda, Toshio: Nonparametric quantile regression with heavy-tailed and strongly dependent errors (2013)
  19. Leng, Chenlei; Tong, Xingwei: A quantile regression estimator for censored data (2013)
  20. Schlittgen, Rainer: Regression analyses with R (2013)

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