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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.

Version: 0.2.0.3
Depends: R (≥ 3.4.0)
Imports: methods, Formula, Rcpp (≥ 0.12.0), rstan (≥ 2.18.1), rstantools (≥ 2.0.0)
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Published: 2023-04-02
DOI: 10.32614/CRAN.package.cbq
Author: Xiao Lu
Maintainer: Xiao LU <xiao.lu.research at gmail.com>
License: MIT + file LICENSE
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README
CRAN checks: cbq results

Documentation:

Reference manual: cbq.pdf

Downloads:

Package source: cbq_0.2.0.3.tar.gz
Windows binaries: r-devel: cbq_0.2.0.3.zip, r-release: cbq_0.2.0.3.zip, r-oldrel: cbq_0.2.0.3.zip
macOS binaries: r-release (arm64): cbq_0.2.0.3.tgz, r-oldrel (arm64): cbq_0.2.0.3.tgz, r-release (x86_64): cbq_0.2.0.3.tgz, r-oldrel (x86_64): cbq_0.2.0.3.tgz
Old sources: cbq archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.