Package: quokar
Title: Quantile Regression Outlier Diagnostics with K Left Out Analysis
Version: 0.1.0
Author: Wenjing Wang <wenjingwangr@gmail.com>, Di Cook <visnut@gmail.com>, Earo Wang <earo.wang@gmail.com>
Maintainer: Wenjing Wang <wenjingwangr@gmail.com>
Description: 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) <arXiv:1509.05099v1>; 
  mean posterior probability and Kullback–Leibler divergence methods for Bayes quantile regression model.
  Reference of this method is Bruno Santos, Heleno Bolfarine (2016) <arXiv:1601.07344v1>.
Depends: R (>= 3.3.0)
License: GPL (>= 2)
Encoding: UTF-8
Imports: stats, quantreg, purrr, magrittr, ALDqr, bayesQR, MCMCpack,
        ggplot2, knitr, gridExtra, GIGrvg, dplyr, tidyr, robustbase,
        ald
Type: Package
NeedsCompilation: yes
LazyLoad: false
VignetteBuilder: knitr
RoxygenNote: 6.0.1
URL: https://github.com/wenjingwang/quokar
BugReports: https://github.com/wenjingwang/quokar/issues
LazyData: true
Suggests: testthat, rmarkdown
Packaged: 2017-11-10 04:38:30 UTC; Thinkpad
Repository: CRAN
Date/Publication: 2017-11-10 10:21:36 UTC
Built: R 3.6.3; x86_64-w64-mingw32; 2020-08-05 06:35:07 UTC; windows
Archs: i386, x64
