Package: qbld 1.0.3

Ayush Agarwal

qbld: Quantile Regression for Binary Longitudinal Data

Implements the Bayesian quantile regression model for binary longitudinal data (QBLD) developed in Rahman and Vossmeyer (2019) <doi:10.1108/S0731-90532019000040B009>. The model handles both fixed and random effects and implements both a blocked and an unblocked Gibbs sampler for posterior inference.

Authors:Ayush Agarwal [aut, cre], Dootika Vats [ctb]

qbld_1.0.3.tar.gz
qbld_1.0.3.tar.gz(r-4.5-noble)qbld_1.0.3.tar.gz(r-4.4-noble)
qbld_1.0.3.tgz(r-4.4-emscripten)qbld_1.0.3.tgz(r-4.3-emscripten)
qbld.pdf |qbld.html
qbld/json (API)

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

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

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

openblascpp

2.00 score 175 downloads 9 exports 49 dependencies

Last updated 3 years agofrom:4df380e6c3. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 10 2024
R-4.5-linux-x86_64NOTEDec 10 2024

Exports:daldmixdgigmodel.qbldpaldmixplot.qbldqaldmixraldmixrgigsummary.qbld

Dependencies:base64encbriobslibcachemcallrclicrayondescdiffobjdigestellipseevaluatefastmapfftwtoolsfontawesomefsgluehighrhtmltoolsjquerylibjsonliteknitrlifecyclemagrittrmcmcsememoisemimemvtnormpkgbuildpkgloadpraiseprocessxpsR6rappdirsRcppRcppArmadilloRcppDistrlangrmarkdownrprojrootsassstableGRtestthattinytexwaldowithrxfunyaml

Using qbld

Rendered fromqbld.Rnwusingknitr::knitron Dec 10 2024.

Last update: 2020-09-10
Started: 2020-09-10

Readme and manuals

Help Manual

Help pageTopics
Quantile Regression for Binary Longitudinal Dataqbld-package qbld
Datasetairpollution
Asymmetric Laplace distributionaldmix daldmix paldmix qaldmix raldmix
Generalised Inverse Gaussiandgig gig rgig
Datasetlocust
QBLD Samplermodel.qbld
Plot QBLDplot.qbld
QBLD Summary Classprint.summary.qbld summary.qbld