Quantile Regression Outlier Diagnostics with K Left Out Analysis

Diagnostics methods for quantile regression models for detecting influential observations: robust distance methods for general quantile regression models; generalized Cook's distance and Q-function distance method for quantile regression models using aymmetric Laplace distribution. Reference of this method can be found in Luis E. Benites, Víctor H. Lachos, Filidor E. Vilca (2015) ; mean posterior probability and Kullback–Leibler divergence methods for Bayes quantile regression model. Reference of this method is Bruno Santos, Heleno Bolfarine (2016) .


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R package for diagnosing quantile regression models

  • quokar can be easily installed on Windows and Linux using command:
devtools::install_github("wenjingwang/quokar")
  • To install quokar on Mac, you need to install a fortran compiler. You can install gfortran by command,
curl -O http://r.research.att.com/libs/gfortran-4.8.2-darwin13.tar.bz2
sudo tar fvxz gfortran-4.8.2-darwin13.tar.bz2 -C /

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Reference manual

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