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 160 articles , 1 standard article )

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  1. Andreas Alfons, Nüfer Y. Ateş, Patrick J. F. Groenen: Robust Mediation Analysis: The R Package robmed (2022) arXiv
  2. Baione, Fabio; Biancalana, Davide: An application of parametric quantile regression to extend the two-stage quantile regression for ratemaking (2021)
  3. Ditzhaus, Marc; Fried, Roland; Pauly, Markus: QANOVA: quantile-based permutation methods for general factorial designs (2021)
  4. Fasiolo, M., Wood, S. N., Zaffran, M., Nedellec, R., Goude, Y. : qgam: Bayesian Nonparametric Quantile Regression Modeling in R (2021) not zbMATH
  5. Frumento, Paolo; Salvati, Nicola: Parametric modeling of quantile regression coefficient functions with count data (2021)
  6. Galarza, Christian E.; Zhang, Panpan; Lachos, Víctor H.: Logistic quantile regression for bounded outcomes using a family of heavy-tailed distributions (2021)
  7. Hudecová, Šárka; Šiman, Miroslav: Testing axial symmetry by means of directional regression quantiles (2021)
  8. Jantre, S. R.; Bhattacharya, S.; Maiti, T.: Quantile regression neural networks: a Bayesian approach (2021)
  9. Jung, Yoonsuh; MacEachern, Steven N.; Joon Kim, Hang: Modified check loss for efficient estimation via model selection in quantile regression (2021)
  10. Maruotti, Antonello; Petrella, Lea; Sposito, Luca: Hidden semi-Markov-switching quantile regression for time series (2021)
  11. Michał Narajewski, Jens Kley-Holsteg, Florian Ziel: tsrobprep - an R package for robust preprocessing of time series data (2021) arXiv
  12. Muggeo, Vito M. R.; Torretta, Federico; Eilers, Paul H. C.; Sciandra, Mariangela; Attanasio, Massimo: Multiple smoothing parameters selection in additive regression quantiles (2021)
  13. Perperoglou, Aris; Huebner, Marianne: Quantile foliation for modelling performance across body mass and age in olympic weightlifting (2021)
  14. Petersen, Lasse; Hansen, Niels Richard: Testing conditional independence via quantile regression based partial copulas (2021)
  15. Pietrosanu, Matthew; Gao, Jueyu; Kong, Linglong; Jiang, Bei; Niu, Di: Advanced algorithms for penalized quantile and composite quantile regression (2021)
  16. Prajual Maheshwari, Mohammad Arshad Rahman: bqror: An R package for Bayesian Quantile Regression in Ordinal Models (2021) arXiv
  17. Santolino, Miguel: Median bilinear models in presence of extreme values (2021)
  18. Brantley, Halley L.; Guinness, Joseph; Chi, Eric C.: Baseline drift estimation for air quality data using quantile trend filtering (2020)
  19. Daniel Fischer, Karl Mosler, Jyrki Möttönen, Klaus Nordhausen, Oleksii Pokotylo, Daniel Vogel: Computing the Oja Median in R: The Package OjaNP (2020) not zbMATH
  20. Güney, Yeşim; Jurečková, Jana; Arslan, Olcay: Averaged autoregression quantiles in autoregressive model (2020)

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