Package: boostmtree 1.5.1
boostmtree: Boosted Multivariate Trees for Longitudinal Data
Implements Friedman's gradient descent boosting algorithm for modeling longitudinal response using multivariate tree base learners. Longitudinal response could be continuous, binary, nominal or ordinal. A time-covariate interaction effect is modeled using penalized B-splines (P-splines) with estimated adaptive smoothing parameter. Although the package is design for longitudinal data, it can handle cross-sectional data as well. Implementation details are provided in Pande et al. (2017), Mach Learn <doi:10.1007/s10994-016-5597-1>.
Authors:
boostmtree_1.5.1.tar.gz
boostmtree_1.5.1.zip(r-4.5)boostmtree_1.5.1.zip(r-4.4)boostmtree_1.5.1.zip(r-4.3)
boostmtree_1.5.1.tgz(r-4.4-any)boostmtree_1.5.1.tgz(r-4.3-any)
boostmtree_1.5.1.tar.gz(r-4.5-noble)boostmtree_1.5.1.tar.gz(r-4.4-noble)
boostmtree_1.5.1.tgz(r-4.4-emscripten)boostmtree_1.5.1.tgz(r-4.3-emscripten)
boostmtree.pdf |boostmtree.html✨
boostmtree/json (API)
NEWS
| # Install 'boostmtree' in R: |
| install.packages('boostmtree', repos = c('https://kogalur.r-universe.dev', 'https://cloud.r-project.org')) |
- AF - Atrial Fibrillation Data
- spirometry - Spirometry Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:b402ee8976. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 19 2024 |
| R-4.5-win | OK | Nov 19 2024 |
| R-4.5-linux | OK | Nov 19 2024 |
| R-4.4-win | OK | Nov 19 2024 |
| R-4.4-mac | OK | Nov 19 2024 |
| R-4.3-win | OK | Nov 19 2024 |
| R-4.3-mac | OK | Nov 19 2024 |
Exports:boostmtreeboostmtree.newsmarginalPlotpartialPlotplot.boostmtreepredict.boostmtreeprint.boostmtreesimLongvimp.boostmtreevimpPlot
Dependencies:base64encbitbit64bslibcachemclicliprcolorspacecpp11crayondata.treeDiagrammeRdigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsgluehighrhmshtmltoolshtmlwidgetsigraphjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimemunsellnlmepillarpkgconfigprettyunitsprogresspurrrR6randomForestSRCrappdirsRColorBrewerreadrrlangrmarkdownrstudioapisassscalesstringistringrtibbletidyrtidyselecttinytextzdbutf8vctrsviridisLitevisNetworkvroomwithrxfunyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Boosted multivariate trees for longitudinal data. | boostmtree-package |
| Atrial Fibrillation Data | AF |
| Boosted multivariate trees for longitudinal data | boostmtree |
| Show the NEWS file | boostmtree.news |
| Marginal plot analysis | marginalPlot |
| Partial plot analysis | partialPlot |
| Plot Summary Analysis | plot.boostmtree |
| Prediction for Boosted multivariate trees for longitudinal data. | predict.boostmtree |
| Print Summary Output | print.boostmtree |
| Simulate longitudinal data | simLong |
| Spirometry Data | spirometry |
| Variable Importance | vimp.boostmtree |
| Variable Importance (VIMP) plot | vimpPlot |
