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

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

## Documentation for package ‘midasml’ version 0.1.11

- DESCRIPTION file

## Help Pages

midasml-package | midasml
alfred_vintages | ALFRED monthly and quarterly series vintages
cv.panel.sglfit | Cross-validation fit for panel sg-LASSO
cv.sglfit | Cross-validation fit for sg-LASSO
dateMatch | Match dates
fa.sglfit | Estimates factor-augmented sparse MIDAS regression model
gb | Gegenbauer polynomials shifted to [a,b]
ic.panel.sglfit | Information criteria fit for panel sg-LASSO
ic.sglfit | Information criteria fit for sg-LASSO
lb | Legendre polynomials shifted to [a,b]
market_ret | SNP500 returns
midas.ardl | MIDAS regression
midasml | midasml
mixed_freq_data | MIDAS data structure
mixed_freq_data_single | MIDAS data structure
monthBegin | Beginning of the month date
monthEnd | End of the month date
predict.cv.panel.sglfit | Computes prediction
predict.cv.sglfit | Computes prediction
predict.fa.sglfit | Computes prediction
predict.ic.panel.sglfit | Computes prediction
predict.ic.sglfit | Computes prediction
predict.sglpath | Computes prediction
reg.panel.sgl | Regression fit for panel sg-LASSO
reg.sgl | Fit for sg-LASSO regression
rgdp_dates | Real GDP release dates
rgdp_vintages | Real GDP vintages
sglfit | Fits sg-LASSO regression
thetafit | Nodewise LASSO regressions to fit the precision matrix Theta
tscv.sglfit | Time series cross-validation fit for sg-LASSO
us_rgdp | US real GDP data with several high-frequency predictors