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 = 'https://cloud.r-project.org')
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

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

openblascpp

2.00 score 243 downloads 9 exports 49 dependencies

Last updated 3 years agofrom:4df380e6c3. Checks:1 OK, 2 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 10 2025
R-4.5-linux-x86_64NOTEMar 10 2025
R-4.4-linux-x86_64NOTEMar 10 2025

Exports:daldmixdgigmodel.qbldpaldmixplot.qbldqaldmixraldmixrgigsummary.qbld

Dependencies:base64encbriobslibcachemcallrclicrayondescdiffobjdigestellipseevaluatefastmapfftwtoolsfontawesomefsgluehighrhtmltoolsjquerylibjsonliteknitrlifecyclemagrittrmcmcsememoisemimemvtnormpkgbuildpkgloadpraiseprocessxpsR6rappdirsRcppRcppArmadilloRcppDistrlangrmarkdownrprojrootsassstableGRtestthattinytexwaldowithrxfunyaml

Using qbld

Rendered fromqbld.Rnwusingknitr::knitron Mar 10 2025.

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

Citation

'qbld' is a package that provides tools for modelling hierarchical Bayesian quantile regression model for binary longitudinal data (QBLD). This version of 'qbld' is currently licensed under the GNU Public License, v3 or later. If you are using 'qbld' for research that will be published, we request that you acknowledge this with the following citation:

Ayush Agarwal (2022). qbld: Quantile Regression for Binary Longitudinal Data. R package version 1.0.3. Indian Institute of Technology, Kanpur.

Corresponding BibTeX entry:

  @Manual{,
    title = {qbld: Quantile Regression for Binary Longitudinal Data},
    author = {Ayush Agarwal},
    year = {2022},
    address = {Indian Institute of Technology, Kanpur},
    note = {R package version 1.0.3},
  }

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