Comments (3)
Hi,
Yes, you can use the package with monthly/daily, weekly/daily, or even intraday data. The key is to create MIDAS structures which can be done by using mixed_freq_data & mixed_freq_data_single functions in the package. Then, you aggregate those using MIDAS polynomials (e.g. Legendre), and run sg-LASSO on stacked covariate matrix.
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Hi Dr. Striaukas,
thank you for providing us such a neat package. I'm trying to run sg-LASSO on a set of monthly covariates to forecast a quarterly variable. I've run mixed_freq_data_single on each of the monthly covariates, but I'm still somewhat confused on how to use the lb command to Legendre-aggregate them before applying cv.sglfit. Could you kindly provide us with a simple example on how to do it?
Thank you so much,
Pedro
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Related Issues (10)
- parallel code for cv.panel.sglfit - typo
- cv.panel.sglfit arguments setting HOT 28
- sglfit standardize issue HOT 1
- Midas regression with daily, monthly and quarterly data HOT 1
- Dynamic forecasting HOT 1
- Wald statistic for the high-dimensional Granger causality tests HOT 1
- midasml Tutorial HOT 1
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