bivarhr: Bivariate Hurdle Regression with Bayesian Model Averaging
Provides tools for fitting bivariate hurdle negative binomial
models with horseshoe priors, Bayesian Model Averaging (BMA) via stacking,
and comprehensive causal inference methods including G-computation,
transfer entropy, Threshold Vector Autoregressive (TVAR) and Smooth
Transition Autoregressive (STAR) models, Dynamic Bayesian Networks (DBN),
Hidden Markov Models (HMM), and sensitivity analysis.
| Version: |
0.1.5 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
stats, utils, grDevices, dplyr (≥ 1.1.0), rlang, data.table (≥ 1.14.0), tidyr, tibble, readr, cli, furrr, future, future.apply, posterior, loo (≥ 2.5.0), progressr |
| Suggests: |
cmdstanr, testthat (≥ 3.0.0), MASS, RTransferEntropy, bnlearn, depmixS4, sensemakr, CausalImpact, bsts, vars, tsDyn, openxlsx, ggplot2, bayesplot, Rgraphviz |
| Published: |
2025-12-19 |
| DOI: |
10.32614/CRAN.package.bivarhr (may not be active yet) |
| Author: |
José Mauricio Gómez Julián
 [aut, cre] |
| Maintainer: |
José Mauricio Gómez Julián <isadore.nabi at pm.me> |
| License: |
MIT + file LICENSE |
| NeedsCompilation: |
no |
| Additional_repositories: |
https://stan-dev.r-universe.dev |
| Materials: |
README, NEWS |
| CRAN checks: |
bivarhr results |
Documentation:
Downloads:
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