Package overview | Setup and data description | Model fitting | Model inspection | Sample plotting | Coefficient plotting | Cross validation
Package: treeDA 0.0.5
treeDA: Tree-Based Discriminant Analysis
Performs sparse discriminant analysis on a combination of node and leaf predictors when the predictor variables are structured according to a tree, as described in Fukuyama et al. (2017) <doi:10.1371/journal.pcbi.1005706>.
Authors:
treeDA_0.0.5.tar.gz
treeDA_0.0.5.zip(r-4.7-any)treeDA_0.0.5.zip(r-4.6-any)treeDA_0.0.5.zip(r-4.5-any)
treeDA_0.0.5.tgz(r-4.6-any)treeDA_0.0.5.tgz(r-4.5-any)
treeDA_0.0.5.tar.gz(r-4.7-any)treeDA_0.0.5.tar.gz(r-4.6-any)
treeDA_0.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
treeDA/json (API)
| # Install 'treeDA' in R: |
| install.packages('treeDA', repos = c('https://jfukuyama.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jfukuyama/treeda/issues
Datasets:
- treeda_example - Example dataset
Last updated from:86ae334c34. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 245 | ||
| source / vignettes | OK | 493 | ||
| linux-release | OK | 358 | ||
| macos-release | OK | 249 | ||
| macos-oldrel | OK | 255 | ||
| windows-devel | OK | 123 | ||
| windows-release | OK | 245 | ||
| windows-oldrel | OK | 153 | ||
| wasm-release | OK | 256 |
Exports:combine_plot_and_treeget_leaf_positionmakeNodeAndLeafPredictorsnodeToLeafCoefficientsplot_coefficientstreedatreedacv
Dependencies:ade4apeBiobaseBiocGenericsbiomformatBiostringsclasscliclustercodetoolscpp11crayondata.tabledigestelasticnetfarverforeachgenericsggplot2gluegtableigraphIRangesisobanditeratorsjsonlitelabelinglarslatticelifecyclemagrittrMASSMatrixmdamgcvmulttestmvtnormnlmepermutephyloseqpixmappkgconfigplyrR6RColorBrewerRcppRcppArmadilloreshape2rlangS4VectorsS7scalesSeqinfospsparseLDAstringistringrsurvivalvctrsveganviridisLitewithrXVector
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Tree-based discriminant analysis | treeDA-package treeDA |
| Coefficients from treeda fit | coef.treeda |
| Method for combining two ggplots | combine_plot_and_tree |
| Get leaf positions from a tree layout | get_leaf_position |
| Make a matrix with predictors for each leaf and node | makeNodeAndLeafPredictors |
| Node coefficients to leaf coefficients | nodeToLeafCoefficients |
| Plot the discriminating axes from treeda | plot_coefficients |
| Plot a treedacv object | plot.treedacv |
| Predict using new data | predict.treeda |
| Print a treeda object | print.treeda |
| Print treedacv objects | print.treedacv |
| Tree-based sparse discriminant analysis | treeda |
| Example dataset | treeda_example |
| treeda cross validation | treedacv |