micvar
Order Selection in Vector Autoregression by Mean Square Information Criteria
Implements order selection for Vector Autoregressive (VAR) models using the Mean Square Information Criterion (MIC). Unlike standard methods such as AIC and BIC, MIC is likelihood-free. This method consistently estimates VAR order and has robust performance under model misspecification. For more details, see Hellstern and Shojaie (2025) <doi:10.48550/arXiv.2511.19761>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | micvar_0.1.0.tar.gz |
27.6 KiB |
0.1.0 |
rolling linux/noble R-4.5 | micvar_0.1.0.tar.gz |
27.5 KiB |
0.1.0 |
rolling source/ R- | micvar_0.1.0.tar.gz |
9.7 KiB |
0.1.0 |
latest linux/jammy R-4.5 | micvar_0.1.0.tar.gz |
27.6 KiB |
0.1.0 |
latest linux/noble R-4.5 | micvar_0.1.0.tar.gz |
27.5 KiB |
0.1.0 |
latest source/ R- | micvar_0.1.0.tar.gz |
9.7 KiB |
0.1.0 |
2026-04-26 source/ R- | micvar_0.1.0.tar.gz |
9.7 KiB |
0.1.0 |
2026-04-23 source/ R- | micvar_0.1.0.tar.gz |
9.7 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | micvar_0.1.0.zip |
30.3 KiB |