LongituRF

Random Forests for Longitudinal Data

CRAN Package

Random forests are a statistical learning method widely used in many areas of scientific research essentially for its ability to learn complex relationships between input and output variables and also its capacity to handle high-dimensional data. However, current random forests approaches are not flexible enough to handle longitudinal data. In this package, we propose a general approach of random forests for high-dimensional longitudinal data. It includes a flexible stochastic model which allows the covariance structure to vary over time. Furthermore, we introduce a new method which takes intra-individual covariance into consideration to build random forests. The method is fully detailled in Capitaine et.al. (2020) doi:10.1177/0962280220946080 Random forests for high-dimensional longitudinal data.

  • Version0.9
  • R versionunknown
  • LicenseGPL-2
  • Needs compilation?No
  • Last release08/31/2020

Team


Insights

Last 30 days

This package has been downloaded 219 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.

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0 downloadsFeb 9, 2025
0 downloadsFeb 10, 2025
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3 downloadsFeb 15, 2025
4 downloadsFeb 16, 2025
8 downloadsFeb 17, 2025
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15 downloadsFeb 20, 2025
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5 downloadsFeb 22, 2025
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8 downloadsMar 1, 2025
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6 downloadsMar 5, 2025
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6 downloadsMar 10, 2025
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3 downloadsMar 14, 2025
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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 3,166 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 45 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

  • Imports4 packages
  • Suggests1 package