bqror
1.7.1Bayesian Quantile Regression for Ordinal Models
Overview
Package provides functions for estimation and inference in Bayesian quantile regression with ordinal outcomes. An ordinal model with 3 or more outcomes (labeled OR1 model) is estimated by a combination of Gibbs sampling and Metropolis-Hastings (MH) algorithm. Whereas an ordinal model with exactly 3 outcomes (labeled OR2 model) is estimated using a Gibbs sampling algorithm. The summary output presents the posterior mean, posterior standard deviation, 95% credible intervals, and the inefficiency factors along with the two model comparison measures – logarithm of marginal likelihood and the deviance information criterion (DIC). The package also provides functions for computing the covariate effects and other functions that aids either the estimation or inference in quantile ordinal models. Rahman, M. A. (2016).“Bayesian Quantile Regression for Ordinal Models.” Bayesian Analysis, 11(1): 1-24 <doi: 10.1214/15-BA939>. Yu, K., and Moyeed, R. A. (2001). “Bayesian Quantile Regression.” Statistics and Probability Letters, 54(4): 437–447 <doi: 10.1016/S0167-7152(01)00124-9>. Koenker, R., and Bassett, G. (1978).“Regression Quantiles.” Econometrica, 46(1): 33-50 <doi: 10.2307/1913643>. Chib, S. (1995). “Marginal likelihood from the Gibbs output.” Journal of the American Statistical Association, 90(432):1313–1321, 1995. <doi: 10.1080/01621459.1995.10476635>. Chib, S., and Jeliazkov, I. (2001). “Marginal likelihood from the Metropolis-Hastings output.” Journal of the American Statistical Association, 96(453):270–281, 2001. <doi: 10.1198/016214501750332848>.
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- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 91%
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Repository
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Checks run against github.com/prajual/bqror on 2026-07-19.
Dependencies
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Code & Tests
Datasets
People & History
16 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
- 1.7.1Latest
- RR 4.4.0 released · 2024-04-24
- 1.7.02024-04-13 · diff ↗
- 1.6.12023-05-06 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 1.6.02023-03-25 · diff ↗
- 1.5.02023-03-14 · diff ↗
- 1.4.02022-07-06 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 1.3.02021-11-22 · diff ↗
- 1.2.02021-09-28 · diff ↗
- 1.1.02021-09-12 · diff ↗
- 0.1.62021-07-23 · diff ↗
- 0.1.52021-07-04 · diff ↗
Package metadata
- First published
- 2020-02-26
- Total releases
- 16 / 6 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 63 KB / 8 files
- Download size
- 114 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet