Package: mtarm 0.1.2
mtarm: Bayesian Estimation of Multivariate Threshold Autoregressive Models
Estimation, inference and forecasting using the Bayesian approach for multivariate threshold autoregressive (TAR) models in which the distribution used to describe the noise process belongs to the class of Gaussian variance mixtures.
Authors:
mtarm_0.1.2.tar.gz
mtarm_0.1.2.zip(r-4.5)mtarm_0.1.2.zip(r-4.4)mtarm_0.1.2.zip(r-4.3)
mtarm_0.1.2.tgz(r-4.4-any)mtarm_0.1.2.tgz(r-4.3-any)
mtarm_0.1.2.tar.gz(r-4.5-noble)mtarm_0.1.2.tar.gz(r-4.4-noble)
mtarm_0.1.2.tgz(r-4.4-emscripten)mtarm_0.1.2.tgz(r-4.3-emscripten)
mtarm.pdf |mtarm.html✨
mtarm/json (API)
| # Install 'mtarm' in R: |
| install.packages('mtarm', repos = c('https://lhvanegasp.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/lhvanegasp/mtar/issues
Datasets:
- returns - Returns of the closing prices of three financial indexes
- riverflows - Rainfall and two river flows in Colombia
Last updated 4 months agofrom:8d47074824. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 20 2024 |
| R-4.5-win | OK | Nov 20 2024 |
| R-4.5-linux | OK | Nov 20 2024 |
| R-4.4-win | OK | Nov 20 2024 |
| R-4.4-mac | OK | Nov 20 2024 |
| R-4.3-win | OK | Nov 20 2024 |
| R-4.3-mac | OK | Nov 20 2024 |
