CRAN/E | quokar

quokar

Quantile Regression Outlier Diagnostics with K Left Out Analysis

Installation

About

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) .

github.com/wenjingwang/quokar
Bug report File report

Key Metrics

Version 0.1.0
R ≥ 3.3.0
Published 2017-11-10 2525 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks quokar results

Downloads

Yesterday 0
Last 7 days 2 -75%
Last 30 days 15 +25%
Last 90 days 45 +32%
Last 365 days 211 -57%

Maintainer

Maintainer

Wenjing Wang

Authors

Wenjing Wang
Di Cook
Earo Wang

Material

README
Reference manual
Package source

Vignettes

'quokar': R package for quantile regression outlier diagnostic

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Depends

R ≥ 3.3.0

Imports

stats
quantreg
purrr
magrittr
ALDqr
bayesQR
MCMCpack
ggplot2
knitr
gridExtra
GIGrvg
dplyr
tidyr
robustbase
ald

Suggests

testthat
rmarkdown