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 39 articles )

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  1. Maistre, Samuel; Lavergne, Pascal; Patilea, Valentin: Powerful nonparametric checks for quantile regression (2017)
  2. Fuzi, Mohd Fadzli Mohd; Jemain, Abdul Aziz; Ismail, Noriszura: Bayesian quantile regression model for claim count data (2016)
  3. Galvao, Antonio F.; Kato, Kengo: Smoothed quantile regression for panel data (2016)
  4. Harrell, Frank E. jun.: Regression modeling strategies. With applications to linear models, logistic regression, and survival analysis (2015)
  5. Mak, T.K.; Nebebe, F.: A parametric approach for estimating conditional probability distributions (2015)
  6. Qoyyimi, Danang Teguh; Zitikis, Ricardas: Measuring association via lack of co-monotonicity: the loc index and a problem of educational assessment (2015)
  7. Valle, C.A.; Meade, N.; Beasley, J.E.: Factor neutral portfolios (2015)
  8. Nash, John C.: Nonlinear parameter optimization using R tools (2014)
  9. Peng, Limin; Xu, Jinfeng; Kutner, Nancy: Shrinkage estimation of varying covariate effects based on quantile regression (2014)
  10. Volgushev, Stanislav; Wagener, Jens; Dette, Holger: Censored quantile regression processes under dependence and penalization (2014)
  11. Alfons, Andreas; Croux, Christophe; Gelper, Sarah: Sparse least trimmed squares regression for analyzing high-dimensional large data sets (2013)
  12. Honda, Toshio: Nonparametric quantile regression with heavy-tailed and strongly dependent errors (2013)
  13. Leng, Chenlei; Tong, Xingwei: A quantile regression estimator for censored data (2013)
  14. Schlittgen, Rainer: Regression analyses with R (2013)
  15. Volgushev, Stanislav; Dette, Holger: Nonparametric quantile regression for twice censored data (2013)
  16. Hay-Jahans, Christopher: An R companion to linear statistical models. (2012)
  17. Kato, Kengo: Asymptotic normality of Powell’s kernel estimator (2012)
  18. Lin, Guixian; He, Xuming; Portnoy, Stephen: Quantile regression with doubly censored data (2012)
  19. Neykov, N.M.; Čížek, P.; Filzmoser, P.; Neytchev, P.N.: The least trimmed quantile regression (2012)
  20. Peng, Limin: Self-consistent estimation of censored quantile regression (2012)

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