varGuidTS
Variance-Guided Time-Series Modeling for Temporal Risk Detection
Fits balanced-panel autoregressive models with conditional heteroscedasticity for temporal risk detection. The main estimator combines autoregressive exogenous mean modeling with GARCH-X variance modeling, subject-specific baseline terms, shared population coefficients, and L1 penalization for high-dimensional covariates. The package returns conditional mean and variance estimates, coefficient summaries, simulations, and exceedance-based risk scores defined as estimated conditional threshold-exceedance probabilities. The implementation builds on the lasso of Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>, generalized autoregressive conditional heteroscedasticity of Bollerslev (1986) <doi:10.1016/0304-4076(86)90063-1>, and L1-regularized high-dimensional time-series modeling of Medeiros and Mendes (2016) <doi:10.1016/j.jeconom.2015.10.011>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.13 |
rolling linux/jammy R-4.5 | varGuidTS_0.1.13.tar.gz |
96.2 KiB |
0.1.13 |
rolling linux/noble R-4.5 | varGuidTS_0.1.13.tar.gz |
96.2 KiB |
0.1.13 |
rolling source/ R- | varGuidTS_0.1.13.tar.gz |
22.3 KiB |
0.1.13 |
latest linux/jammy R-4.5 | varGuidTS_0.1.13.tar.gz |
96.2 KiB |
0.1.13 |
latest linux/noble R-4.5 | varGuidTS_0.1.13.tar.gz |
96.2 KiB |
0.1.13 |
latest source/ R- | varGuidTS_0.1.13.tar.gz |
22.3 KiB |
0.1.13 |
2026-04-23 source/ R- | varGuidTS_0.1.13.tar.gz |
0 B |