Estimation and Prediction Methods for High-Dimensional Mixed Frequency Time Series Data

The 'midasml' estimation and prediction methods for high dimensional time series regression models under mixed data sampling data structures using structured-sparsity penalties and orthogonal polynomials. For more information on the 'midasml' approach see Babii, Ghysels, and Striaukas (2020) . Functions that compute MIDAS data structures were inspired by MIDAS 'Matlab' toolbox (v2.3) written by Eric Ghysels.


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install.packages("midasml")

0.0.5 by Jonas Striaukas, 4 months ago


Report a bug at https://github.com/jstriaukas/midasml/issues


Browse source code at https://github.com/cran/midasml


Authors: Jonas Striaukas [aut, cre]


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, lubridate, parallel, doSNOW, stats, optimx, quantreg

Depends on foreach

Linking to Rcpp, RcppArmadillo


See at CRAN