DBR
1.4.1Discrete Beta Regression
Overview
Bayesian Beta Regression, adapted for bounded discrete responses, commonly seen in survey responses. Estimation is done via Markov Chain Monte Carlo sampling, using a Gibbs wrapper around univariate slice sampler (Neal (2003) DOI:10.1214/aos/1056562461), as implemented in the R package MfUSampler (Mahani and Sharabiani (2017) <DOI: 10.18637/jss.v078.c01>).
Install
Health
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Downloads
Dependencies
Nothing depends on this yet.
Code & Tests
- Cyclomatic complexity
- 1.5 median / 8 max
- Documented parameters
- 95%
Test coverage
Line coverage
–
Expression
–
Tests / Examples
–
Functions
22 3 exported
Complexity
2.2 avg / 8 max
Call network
22 nodes / 5 edges
Test coverage has not been measured for this package yet; nodes fall back to a neutral fill.
Call graph
Open call graph →Lowest coverage
Per-function coverage is not measured for this package yet.
People & History
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Package metadata
- First published
- 2022-03-23
- Total releases
- 5 / 4 yrs
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 5.5 KB / 1 file
- Download size
- 851 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet