Package: HVT 26.1.3

Zubin Dowlaty

HVT: Constructing Hierarchical Voronoi Tessellations and Overlay Heatmaps for Data Analysis

Facilitates building topology preserving maps for data analysis.

Authors:Zubin Dowlaty [aut, cre], Mu Sigma, Inc. [cph]

# Install 'HVT' in R:

install.packages('HVT', repos = c('https://mu-sigma.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Last updated from:6028814813. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel	OK	242
source / vignettes	OK	365
linux-release	OK	207
macos-release	OK	217
macos-oldrel	OK	250
windows-devel	OK	158
windows-release	OK	189
windows-oldrel	OK	181
wasm-release	OK	155

Last update: 2026-04-29
Started: 2023-10-18

Help page	Topics
Performing Hierarchical Clustering Analysis	clustHVT
function for displaying table	displayTable
plots for data analysis	edaPlots
Creating Transition Probability Matrix	getTransitionProbability
HVT-MSM Optimization Function	HVTMSMoptimization
Performing Monte Carlo Simulations of Markov Chain	msm
Table display of all combinations performed in `HVTMSMoptimization`	OptimizationResults
Generating flow maps and animations based on transition probabilities	plotAnimatedFlowmap
Ex-ante raw series forecasting	plotExAnteRawSeries
Plot the hierarchical tessellations.	plotHVT
Make the diagnostic plots for hierarchical voronoi tessellations	plotModelDiagnostics
plotting MAE across Number of cells	plotMsmKN
Plot the identified outlier cells in the voronoi tessellation map.	plotNovelCells
Make the quantization error plots for training and scoring.	plotQuantErrorHistogram
Creating State Transition Plot	plotStateTransition
Plots of z scores	plotZscore
Reconciliation of Transition Probability	reconcileTransitionProbability
Remove identified novelty cell(s)	removeNovelty
Score which cell each point in the test dataset belongs to.	scoreHVT
Score which cell and what layer each data point in the test dataset belongs to	scoreLayeredHVT
Table for displaying summary	summary
Constructing Hierarchical Voronoi Tessellations	trainHVT