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MultiKink (version 0.1.0)

Estimation and Inference for Multi-Kink Quantile Regression

Description

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".

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Version

Install

install.packages('MultiKink')

Monthly Downloads

195

Version

0.1.0

License

GPL

Maintainer

Chuang Wan

Last Published

May 4th, 2020

Functions in MultiKink (0.1.0)

fit.control

Auxiliary parameters to control the model fitting.
mkqr.bea

Fit the multi-kink quantile regression in absence of the number of change points.
triceps

Triceps skinfold thichness dataset
mkqr.fit

Fit the multi-kink quantile regression conditonal on a given or pre-specified number of change points.
kinkTest

Test the existence of kink effect in the multi-kink quantile regression