Package: cbq 0.2.0.4

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:
cbq_0.2.0.4.tar.gz
cbq_0.2.0.4.tar.gz(r-4.5-noble)cbq_0.2.0.4.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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 13 days agofrom:50ac7dbf33. Checks:2 OK, 1 NOTE. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 06 2025 |
R-4.5-linux-x86_64 | OK | Mar 06 2025 |
R-4.4-linux-x86_64 | NOTE | Mar 06 2025 |
Exports:cbqdaldpaldplot_coef.cbqplot_trace.cbqprint_coef.cbqprint_mcmc.cbqprint_text.cbqqaldrald
Dependencies:abindbackportsBHcallrcheckmateclicolorspacedescdistributionalfansifarverFormulagenericsggplot2gluegridExtragtableinlineisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsscalesStanHeaderstensorAtibbleutf8vctrsviridisLitewithr