A Fast Algorithm for Kernel Quantile Regression

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Documentation for package ‘fastkqr’ version 1.0.1

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package NEWS

Help Pages

coef.cv.fastlqr	Extract Coefficients from a cv.fastlqr Object
coef.fastlqr	Extract Coefficients from a fastlqr Object
coef.kqr	Extract model coefficients from a 'kqr' object.
coef.nckqr	Extract model coefficients from a 'nckqr' object.
cv.kqr	cross-validation for selecting the tuning parameter of kernel quantile regression
cv.nckqr	cross-validation for selecting the tuning parameter 'lambda2' of non-crossing kernel quantile regression
cv.qr	Cross-Validation for Regularized Linear Quantile Regression
kqr	Solve the kernel quantile regression. The solution path is computed at a grid of values of tuning parameter 'lambda'.
nckqr	Solve the non-crossing kernel quantile regression
predict.cv.fastlqr	Predict from a cv.fastlqr Object
predict.fastlqr	Predict from a fastlqr Object
predict.kqr	Predict the fitted values for a 'kqr' object.
predict.nckqr	Predict the fitted values for a 'nckqr' object.
qr	Regularized Linear Quantile Regression