FDboost
Boosting Functional Regression Models
Regression models for functional data, i.e., scalar-on-function, function-on-scalar and function-on-function regression models, are fitted by a component-wise gradient boosting algorithm. For a manual on how to use 'FDboost', see Brockhaus, Ruegamer, Greven (2017) doi:10.18637/jss.v094.i10.
- Version1.1-2
- R version≥ 3.5.0
- LicenseGPL-2
- Needs compilation?No
- FDboost citation info
- Last release08/12/2023
Documentation
Team
David Ruegamer
MaintainerShow author detailsTorsten Hothorn
Show author detailsRolesContributorSarah Brockhaus
Show author detailsRolesAuthorAlmond Stoecker
Show author detailsRolesAuthorwith contributions by many others (see inst/CONTRIBUTIONS)
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 842 times in the last 30 days. Not bad! The download count is somewhere between 'small-town buzz' and 'moderate academic conference'. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 43 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 11,621 times in the last 365 days. The academic equivalent of having a dedicated subreddit. There are fans, and maybe even a few trolls! The day with the most downloads was Nov 05, 2024 with 90 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
- Depends1 package
- Imports6 packages
- Suggests8 packages
- Reverse Suggests2 packages