Package index • hvtiBoostmtree

Core Modelling

Fit and predict boosted multivariate tree models for longitudinal data.

boostmtree(): Boosted multivariate trees for longitudinal data
predict(<boostmtree>): Prediction for Boosted multivariate trees for longitudinal data.
plot(<profile.prx>): Plot Proximity Profile for a profile.prx Object

Model Inspection

Print summaries and produce diagnostic plots for fitted models.

print(<boostmtree>): Print Summary Output
plot(<boostmtree>): Plot Summary Analysis

Variable Importance

Compute and visualise permutation-based variable importance scores.

vimp.boostmtree(): Variable Importance
vimpPlot(): Variable Importance (VIMP) plot

Dependence Plots

Explore covariate effects via marginal and partial dependence plots.

marginalPlot(): Marginal plot analysis
partialPlot(): Partial plot analysis

Data Simulation

Generate synthetic longitudinal datasets for benchmarking and testing.

simLong(): Simulate longitudinal data

Datasets

Real-world longitudinal datasets bundled with the package.

AF: Atrial Fibrillation Data
spirometry: Spirometry Data

Package

Package-level documentation and utilities.

hvtiBoostmtree hvtiBoostmtree-package: Boosted multivariate trees for longitudinal data.
boostmtree.news(): Show the NEWS file