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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.3 |
rolling linux/jammy R-4.5 | qbld_1.0.3.tar.gz |
515.5 KiB |
1.0.3 |
rolling linux/noble R-4.5 | qbld_1.0.3.tar.gz |
518.4 KiB |
1.0.3 |
rolling source/ R- | qbld_1.0.3.tar.gz |
332.9 KiB |
1.0.3 |
latest linux/jammy R-4.5 | qbld_1.0.3.tar.gz |
515.5 KiB |
1.0.3 |
latest linux/noble R-4.5 | qbld_1.0.3.tar.gz |
518.4 KiB |
1.0.3 |
latest source/ R- | qbld_1.0.3.tar.gz |
332.9 KiB |
1.0.3 |
2026-04-26 source/ R- | qbld_1.0.3.tar.gz |
332.9 KiB |
1.0.3 |
2026-04-23 source/ R- | qbld_1.0.3.tar.gz |
332.9 KiB |
1.0.3 |
2026-04-09 windows/windows R-4.5 | qbld_1.0.3.zip |
836.9 KiB |
1.0.3 |
2025-04-20 source/ R- | qbld_1.0.3.tar.gz |
332.9 KiB |