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midasml
View on CRAN: Click
here
Download and install midasml package within the R console
Install from CRAN:
install.packages("midasml")
Install from Github:
library("remotes")
install_github("cran/midasml") Install by package version:
library("remotes")
install_version("midasml", "0.1.11") Attach the package and use:
library("midasml")
Maintained by
Jonas Striaukas
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-25
Latest Update: 2022-04-29
Description:
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) . 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.
How to cite:
Jonas Striaukas (2020). midasml: Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data. R package version 0.1.11, https://cran.r-project.org/web/packages/midasml. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.0.1 (2020-06-25 18:10), 0.0.2 (2020-07-01 14:00), 0.0.3 (2020-07-03 18:40), 0.0.4 (2020-07-05 00:50), 0.0.5 (2020-07-05 23:20), 0.0.6 (2021-03-13 00:00), 0.1.0 (2021-04-14 14:00), 0.1.2 (2021-04-22 02:10), 0.1.3 (2021-04-22 16:00), 0.1.4 (2021-04-23 17:00), 0.1.5-1 (2021-05-20 10:30), 0.1.5 (2021-05-05 16:40), 0.1.6 (2021-11-30 15:30), 0.1.7 (2021-12-08 14:00), 0.1.8 (2021-12-16 10:00), 0.1.9-1 (2022-02-15 20:20), 0.1.9 (2022-01-10 14:22), 0.1.10 (2022-04-29 09:00)
Other packages that cited midasml R package
View midasml citation profile
Other R packages that midasml depends,
imports, suggests or enhances
Complete documentation for midasml
Functions, R codes and Examples using
the midasml R package
Some associated functions: alfred_vintages . cv.panel.sglfit . cv.panel.sglpath . cv.sglfit . cv.sglpath . data_freq . dateMatch . date_vec . diff_time_mf . gb . ic.panel.sglfit . ic.pen . ic.sglfit . lag_num . lb . market_ret . midas.ardl . midasml-package . mixed_freq_data . mixed_freq_data_single . mode_midasml . monthBegin . monthEnd . predict.cv.panel.sglfit . predict.cv.sglfit . predict.ic.panel.sglfit . predict.ic.sglfit . predict.sglpath . reg.panel.sgl . reg.sgl . rgdp_dates . rgdp_vintages . sglfit . thetafit . tscv.sglfit . tscv.sglpath . us_rgdp .
Some associated R codes: cv.panel.sglfit.R . cv.sglfit.R . data.R . date.functions.R . ic.panel.sglfit.R . ic.sglfit.R . midas.polynomials.R . midas.solvers.R . midasml-package.R . predict.cv.sglfit.R . predict.ic.sglfit.R . predict.sglpath.R . reg.midas.R . reg.panel.sgl.R . reg.sgl.R . sglfit.R . sglfitpath.R . thetafit.R . tscv.sglfit.R . utilities.R . Full midasml package functions and examples
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