qbld
1.0.3Quantile Regression for Binary Longitudinal Data
Overview
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.
Install
Health
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- NOTE2026-05-110 OK · 13 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- WARNING2026-05-100 OK · 12 NOTE · 1 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-04-220 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-180 OK · 13 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-100 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 64%
- Return-value docs
- 100%
- References docs
- 88%
Downloads
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Code & Tests
Datasets
People & History
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3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- 1.0.3Latest
- unarchivedReturned to CRAN2022-01-06
- archivedRemoved from CRAN2021-10-07required archived package 'stableGR'
- RR 4.1.0 released · 2021-05-18
- 1.0.12020-09-11 · diff ↗
- 1.02020-09-10
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2020-09-10
- Total releases
- 3 / 6 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5
- Bundled data
- 2.2 KB / 2 files
- Download size
- 333 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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