MultiKink: Estimation and Inference for Multi-Kink Quantile Regression

Estimation and inference for multiple kink quantile regression. A bootstrap restarting iterative segmented quantile algorithm is proposed to estimate the multiple kink quantile regression model conditional on a given number of change points. The number of kinks is also allowed to be unknown. In such case, the backward elimination algorithm and the bootstrap restarting iterative segmented quantile algorithm are combined to select the number of change points based on a quantile BIC. A score-type based test statistic is also developed for testing the existence of kink effect. The package is based on the paper, "Wei Zhong, Chuang Wan and Wenyang Zhang (2020). Estimation and inference for multi-kink quantile regression, submitted".

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: quantreg, MASS
Published: 2020-05-04
Author: Chuang Wan [aut, cre], Wei Zhong [aut]
Maintainer: Chuang Wan <wanchuang at stu.xmu.edu.cn>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
CRAN checks: MultiKink results

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Reference manual: MultiKink.pdf
Package source: MultiKink_0.1.0.tar.gz
Windows binaries: r-devel: MultiKink_0.1.0.zip, r-release: MultiKink_0.1.0.zip, r-oldrel: MultiKink_0.1.0.zip
macOS binaries: r-release (arm64): MultiKink_0.1.0.tgz, r-release (x86_64): MultiKink_0.1.0.tgz, r-oldrel: MultiKink_0.1.0.tgz

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