midasml
Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data
The 'midasml' package implements estimation and prediction methods for high-dimensional mixed-frequency (MIDAS) time-series and panel data regression models. The regularized MIDAS models are estimated using orthogonal (e.g. Legendre) polynomials and sparse-group LASSO (sg-LASSO) estimator. For more information on the 'midasml' approach see Babii, Ghysels, and Striaukas (2021, JBES forthcoming) <doi:10.1080/07350015.2021.1899933>. The package is equipped with the fast implementation of the sg-LASSO estimator by means of proximal block coordinate descent. High-dimensional mixed frequency time-series data can also be easily manipulated with functions provided in the package.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.11 |
rolling linux/jammy R-4.5 | midasml_0.1.11.tar.gz |
915.9 KiB |
0.1.11 |
rolling linux/noble R-4.5 | midasml_0.1.11.tar.gz |
915.7 KiB |
0.1.11 |
rolling source/ R- | midasml_0.1.11.tar.gz |
702.4 KiB |
0.1.11 |
latest linux/jammy R-4.5 | midasml_0.1.11.tar.gz |
915.9 KiB |
0.1.11 |
latest linux/noble R-4.5 | midasml_0.1.11.tar.gz |
915.7 KiB |
0.1.11 |
latest source/ R- | midasml_0.1.11.tar.gz |
702.4 KiB |
0.1.11 |
2026-04-26 source/ R- | midasml_0.1.11.tar.gz |
702.4 KiB |
0.1.11 |
2026-04-23 source/ R- | midasml_0.1.11.tar.gz |
702.4 KiB |
0.1.11 |
2026-04-09 windows/windows R-4.5 | midasml_0.1.11.zip |
1.1 MiB |
0.1.10 |
2025-04-20 source/ R- | midasml_0.1.10.tar.gz |
698.8 KiB |