DREGAR
Regularized Estimation of Dynamic Linear Regression in the Presence of Autocorrelated Residuals (DREGAR)
A penalized/non-penalized implementation for dynamic regression in the presence of autocorrelated residuals (DREGAR) using iterative penalized/ordinary least squares. It applies Mallows CP, AIC, BIC and GCV to select the tuning parameters.
- Version0.1.3.0
- R version≥ 2.10.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release03/10/2017
Documentation
Team
Hamed Haselimashhadi
Insights
Last 30 days
This package has been downloaded 400 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 4 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 6,356 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Sep 11, 2024 with 59 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports1 package