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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

VersionRepositoryFileSize
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

Dependencies (latest)

Imports

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