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qrsvm (version 0.2.1)

SVM Quantile Regression with the Pinball Loss

Description

Quantile Regression (QR) using Support Vector Machines under the Pinball-Loss. Estimation is based on "Nonparametric Quantile Regression" by I. Takeuchi, Q.V.Le , T. Sears, A.J.Smola (2004). Implementation relies on 'quadprog' package, package 'kernlab' Kernelfunctions and package 'Matrix' nearPD to find next Positive definite Kernelmatrix. Package estimates quantiles individually but an Implementation of non crossing constraints coming soon. Function multqrsvm() now supports parallel backend for faster fitting.

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Version

Install

install.packages('qrsvm')

Monthly Downloads

1

Version

0.2.1

License

GPL-2

Maintainer

Thilo Hofmeister

Last Published

May 10th, 2017

Functions in qrsvm (0.2.1)

predict.multqrsvm

Predict an Object of class "multqrsvm"
predict.qrsvm

Predict an Object of class "qrsvm"
qrsvm

Fits a quantile regression SVM based on the Pinball Loss
kernelMat

Modified KernelMatrix function to produce less errors
multqrsvm

Fits multiple Quantile Regression SVM