
CAViaR
 Referenced in 142 articles
[sw04424]
 Conditional autoregressive value at risk by regression quantiles. Value at risk (VaR) is the standard ... process and estimates the parameters with regression quantiles. Utilizing the criterion that each period...

quantreg
 Referenced in 142 articles
[sw04356]
 package quantreg: Quantile Regression. Estimation and inference methods for models of conditional quantiles: Linear...

np
 Referenced in 92 articles
[sw10543]
 parametric mean regression models and parametric quantile regression models, among others. The np package focuses...

Kernlab
 Referenced in 89 articles
[sw07926]
 classification, regression, clustering, novelty detection, quantile regression and dimensionality reduction. Among other methods kernlab includes...

rms
 Referenced in 88 articles
[sw04532]
 with binary or ordinal logistic regression, Cox regression, accelerated failure time models, ordinary linear models ... correlated observations, generalized linear models, and quantile regression...

gbm
 Referenced in 50 articles
[sw07994]
 squares, absolute loss, tdistribution loss, quantile regression, logistic, multinomial logistic, Poisson, Cox proportional hazards...

AS 229
 Referenced in 27 articles
[sw26296]
 Algorithm AS 229: computing regression quantiles...

cmprskQR
 Referenced in 17 articles
[sw11076]
 cmprskQR: Analysis of Competing Risks Using Quantile Regressions. Estimation, testing and regression modeling of subdistribution ... functions in competing risks using quantile regressions, as described in Peng and Fine ... Competing risks quantile regression, JASA...

bmrm
 Referenced in 20 articles
[sw11016]
 beta optimization, ROC optimization, ordinal regression, quantile regression, epsilon insensitive regression, least mean square, logistic...

Expectreg
 Referenced in 14 articles
[sw14660]
 package expectreg: Expectile and Quantile Regression. Expectile and quantile regression of models with nonlinear effects...

QICD
 Referenced in 12 articles
[sw19679]
 Coefficients for NonConvex Penalized Quantile Regression Model by using QICD Algorithm. Extremely fast algorithm ... Algorithm for Highdimensional Nonconvex Penalized Quantile Regression. This algorithm combines the coordinate descent algorithm ... cross validation and BIC for quantile regression model. Details are described in Peng...

grf
 Referenced in 8 articles
[sw27871]
 methods for nonparametric leastsquares regression, quantile regression, and treatment effect estimation (optionally using...

bayesQR
 Referenced in 7 articles
[sw11009]
 package bayesQR: Bayesian quantile regression. Bayesian quantile regression using the asymmetric Laplace distribution, both continuous...

lqmm
 Referenced in 10 articles
[sw14399]
 collection of functions to fit quantile regression models for independent and hierarchical data...

qrcm
 Referenced in 5 articles
[sw16728]
 Parametric modeling of quantile regression coefficient functions. Estimating the conditional quantiles of outcome variables ... frequent in many research areas, and quantile regression is foremost among the utilized methods ... coefficients of a quantile regression model depend on the order of the quantile being estimated ... modeling the regression coefficients as parametric functions of the order of the quantile. This approach...

Quantregforest
 Referenced in 5 articles
[sw14249]
 quantregForest: Quantile Regression Forests. Quantile Regression Forests is a treebased ensemble method for estimation...

rqPen
 Referenced in 5 articles
[sw19266]
 package rqPen: Penalized Quantile Regression. Performs penalized quantile regression for LASSO, SCAD and MCP functions...

factorQR
 Referenced in 5 articles
[sw06063]
 factorQR: Bayesian quantile regression factor models , Package to fit Bayesian quantile regression models that assume...

Brq
 Referenced in 4 articles
[sw23416]
 package Brq: Bayesian Analysis of Quantile Regression Models. Bayesian estimation and variable selection for quantile...

cqrReg
 Referenced in 3 articles
[sw21332]
 Package for Quantile and Composite Quantile Regression and Variable Selection. The cqrReg package ... regression models for quantile and composite quantile regression, both with and without an adaptive lasso ... this paper, we reformulate these quantile regression problems and present the estimators we implement ... publiclyavailable methods for (composite) quantile regression, both with and without regularization. We demonstrate...