Package: cbq 0.2.0.3

Xiao LU

cbq: Conditional Binary Quantile Models

Estimates conditional binary quantile models developed by Lu (2020) <doi:10.1017/pan.2019.29>. The estimation procedure is implemented based on Markov chain Monte Carlo methods.

Authors:Xiao Lu

cbq_0.2.0.3.tar.gz
cbq_0.2.0.3.tar.gz(r-4.5-noble)cbq_0.2.0.3.tar.gz(r-4.4-noble)
cbq.pdf |cbq.html
cbq/json (API)

# Install 'cbq' in R:
install.packages('cbq', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

10 exports 0.00 score 54 dependencies 1 scripts 306 downloads

Last updated 1 years agofrom:3e8ccd8e33. Checks:OK: 1 NOTE: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 27 2024
R-4.5-linux-x86_64NOTEAug 27 2024

Exports:cbqdaldpaldplot_coef.cbqplot_trace.cbqprint_coef.cbqprint_mcmc.cbqprint_text.cbqqaldrald

Dependencies:abindbackportsBHcallrcheckmateclicolorspacedescdistributionalfansifarverFormulagenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeaderstensorAtibbleutf8vctrsviridisLitewithr