Package: HistDAWass 1.0.10

Antonio Irpino

HistDAWass: Histogram-Valued Data Analysis

In the framework of Symbolic Data Analysis, a relatively new approach to the statistical analysis of multi-valued data, we consider histogram-valued data, i.e., data described by univariate histograms. The methods and the basic statistics for histogram-valued data are mainly based on the L2 Wasserstein metric between distributions, i.e., the Euclidean metric between quantile functions. The package contains unsupervised classification techniques, least square regression and tools for histogram-valued data and for histogram time series. An introducing paper is Irpino A. Verde R. (2015) <doi:10.1007/s11634-014-0176-4>.

Authors:Antonio Irpino [aut, cre]

HistDAWass_1.0.10.tar.gz
HistDAWass_1.0.10.zip(r-4.7-x86_64)HistDAWass_1.0.10.zip(r-4.7-arm64)HistDAWass_1.0.10.zip(r-4.6-x86_64)HistDAWass_1.0.10.zip(r-4.6-arm64)
HistDAWass_1.0.10.tar.gz(r-4.7-arm64)HistDAWass_1.0.10.tar.gz(r-4.7-x86_64)HistDAWass_1.0.10.tar.gz(r-4.6-arm64)HistDAWass_1.0.10.tar.gz(r-4.6-x86_64)
HistDAWass_1.0.10.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
HistDAWass/json (API)

# Install 'HistDAWass' in R:
install.packages('HistDAWass', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/airpino/histdawass/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library
Datasets:

On CRAN:

Conda:

openblascppopenmp

5.68 score 2 stars 1 packages 53 scripts 590 downloads 3 mentions 68 exports 114 dependencies

Last updated from:6c314e330f. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK167
linux-devel-x86_64OK222
source / vignettesOK280
linux-release-arm64OK167
linux-release-x86_64OK190
windows-devel-arm64OK313
windows-devel-x86_64OK233
windows-release-arm64OK286
windows-release-x86_64OK198
wasm-releaseOK140

Exports:Center.cell.MatHcheckEmptyBinscompPcompQcrwtransformdata2histdistributionHdotpWDouglasPeuckerget.cell.MatHget.distrget.histoget.mget.MatH.main.infoget.MatH.ncolsget.MatH.nrowsget.MatH.rownamesget.MatH.statsget.MatH.varnamesget.sHTS.exponential.smoothingHTS.moving.averagesHTS.predict.knnis.registeredMHkurtHMatHmeanHplotplot_errorsplotPredVsObsregisterregisterMHrQQset.cell.MatHShortestDistanceskewHstdHsubsetHTSsummaryHTSWassSqDistHWH_2d_Adaptive_Kohonen_mapsWH_2d_Kohonen_mapsWH_adaptive_fcmeansWH_adaptive.kmeansWH_fcmeansWH_hclustWH_kmeansWH_MAT_DISTWH.1d.PCAWH.bindWH.bind.colWH.bind.rowWH.correlationWH.correlation2WH.mat.prodWH.mat.sumWH.MultiplePCAWH.plot_multiple_indivsWH.plot_multiple_Spanish.funsWH.regression.GOFWH.regression.two.componentsWH.regression.two.components.predictWH.SSQWH.SSQ2WH.var.covarWH.var.covar2WH.vec.meanWH.vec.sum

Dependencies:abindbackportsbase64encbootbroombslibcachemcarcarDataclasscliclustercolorspacecowplotcpp11crosstalkDerivdigestdoBydplyrDTellipseemmeansestimabilityevaluateFactoMineRfarverfastmapflashClustfontawesomeforecastFormulafracdifffsgenericsggplot2ggrepelggridgesgluegtablehighrhistogramhtmltoolshtmlwidgetsirlbaisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevalleapslifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmemoisemgcvmimeminqamodelrmultcompViewmvtnormnlmenloptrnnetnumDerivotelpbkrtestpillarpkgconfigpromisespurrrquantregR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrmarkdownS7sassscalesscatterplot3dshowtextshowtextdbSparseMstringistringrsurvivalsysfontstibbletidyrtidyselecttimeDatetinytexurcautf8vctrsviridisLitewithrxfunyamlzoo

Creating histogram-valued data
A single histogram | From raw data to a histogram | A matrix of histograms | From a data frame of raw data | Working with a MatH | Registration | Histogram time series
Rendered fromHistDAWass-01-data.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-10-29

Basic statistics for histogram data
Statistics of a single histogram | Arithmetic and distance between two histograms | Statistics of each histogram of a matrix | Mean histogram, variance, covariance and correlation of the variables | Distances between individuals | Reference
Rendered fromHistDAWass-02-basic-statistics.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-10-29

Clustering histogram data: k-means and fuzzy c-means
K-means | Choosing the number of clusters | K-means with adaptive distances | Fuzzy c-means | Fuzzy c-means with adaptive distances | Comparing partitions | References
Rendered fromHistDAWass-03-clustering.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-10-29

Principal component analysis of histogram data
PCA of one histogram variable | PCA of several histogram variables | Reference
Rendered fromHistDAWass-04-pca.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-10-29

Linear regression of histogram variables
The two-component model | Fitting the model | Predictions and goodness of fit | Plotting observed and predicted histograms | Simplified computations | Reference
Rendered fromHistDAWass-05-regression.Rmdusingknitr::rmarkdown

Last update: 2026-10-29
Started: 2026-10-29

Readme and manuals

Help Manual

Help pageTopics
HistDAWass: Histogram-Valued Data AnalysisHistDAWass-package HistDAWass
Age pyramids of the countries of the World in 2014Age_Pyramids_2014
Agronomique dataAgronomique
Arithmetic operators for histograms*,distributionH,distributionH-method *,distributionH,numeric-method *,numeric,distributionH-method +,distributionH,distributionH-method +,distributionH,numeric-method +,numeric,distributionH-method -,distributionH,distributionH-method -,distributionH,numeric-method -,numeric,distributionH-method Arith-distributionH
Blood dataBLOOD
Blood data from BritoBloodBRITO
Centre the histograms of a matrixCenter.cell.MatH Center.cell.MatH,MatH-method
Fix the empty bins of histogramscheckEmptyBins checkEmptyBins,distributionH-method checkEmptyBins,MatH-method
Monthly climatic data of ChinaChina_Month
Seasonal climatic data of ChinaChina_Seas
Cumulative distribution function of a histogram at a valuecompP compP,distributionH,numeric-method
Quantile of a histogramcompQ compQ,distributionH,numeric-method
Centres, radii and weights of the bins of a histogramcrwtransform crwtransform,distributionH-method
Build a histogram from raw datadata2hist
Histogram objects: the distributionH classdistributionH distributionH-class initialize,distributionH-method
Dot product of two histogramsdotpW dotpW,distributionH,distributionH-method dotpW,distributionH,numeric-method dotpW,numeric,distributionH-method
Ramer-Douglas-Peucker algorithmDouglasPeucker
Extract a sub-matrix of histogramsextract-MatH [,MatH,ANY,ANY,ANY-method [,MatH-method
Get or set a cell of a matrix of histogramsget.cell.MatH get.cell.MatH,MatH,numeric,numeric-method set.cell.MatH set.cell.MatH,distributionH,MatH,numeric,numeric-method
Cumulative distribution function of a histogramget.distr get.distr,distributionH-method
Bins of a histogramget.histo get.histo,distributionH-method
Mean of a histogram (stored value)get.m get.m,distributionH-method
Dimensions and names of a matrix of histogramsget.MatH.main.info get.MatH.main.info,MatH-method get.MatH.ncols get.MatH.ncols,MatH-method get.MatH.nrows get.MatH.nrows,MatH-method get.MatH.rownames get.MatH.rownames,MatH-method get.MatH.varnames get.MatH.varnames,MatH-method
Statistics of the histograms of a matrixget.MatH.stats get.MatH.stats,MatH-method
Standard deviation of a histogram (stored value)get.s get.s,distributionH-method
Histogram time series: the HTS classHTS-class initialize,HTS-method
Exponential smoothing of a histogram time seriesHTS.exponential.smoothing
Moving averages of a histogram time seriesHTS.moving.averages
K-NN forecast of a histogram time seriesHTS.predict.knn
Kurtosis of a histogramkurtH kurtH,distributionH-method
Matrices of histograms: the MatH classinitialize,MatH-method MatH MatH-class
Mean of a histogrammeanH meanH,distributionH-method
Ozone data (stations without missing data)OzoneFull
Ozone data (all the stations)OzoneH
Plot the errors of predicted histogramsplot_errors
Plot a histogramplot,distributionH-method plot-distributionH
Plot a histogram time seriesplot,HTS-method plot-HTS
Plot a matrix of histogramsplot,MatH-method plot-MatH
Plot a histogram with a time referenceplot,TdistributionH-method plot-TdistributionH
Plot observed versus predicted histogramsplotPredVsObs
Register two histograms on a common cdfregister register,distributionH,distributionH-method
Register the histograms of a matrix on a common cdfis.registeredMH is.registeredMH,MatH-method registerMH registerMH,MatH-method
Histogram time series of returnsRetHTS
Correlation between the quantile functions of two histogramsrQQ rQQ,distributionH,distributionH-method
Distance between a point and a lineShortestDistance
Print a histogramshow,distributionH-method show-distributionH
Print a matrix of histogramsshow,MatH-method show-MatH
Skewness of a histogramskewH skewH,distributionH-method
Coordinates of the stations of the China datasetsstations_coordinates
Standard deviation of a histogramstdH stdH,distributionH-method
Subset of a histogram time seriessubsetHTS subsetHTS,HTS,numeric,numeric-method
Summary statistics of a histogram time seriessummaryHTS
Histograms with a time reference: the TdistributionH classinitialize,TdistributionH-method TdistributionH-class
Matrices of histograms with a time reference: the TMatH classinitialize,TMatH-method TMatH-class
Squared L2 Wasserstein distance between two histogramsWassSqDistH WassSqDistH,distributionH,distributionH-method
Batch Kohonen self-organising maps of histogram data with adaptive distancesWH_2d_Adaptive_Kohonen_maps
Batch Kohonen self-organising maps of histogram dataWH_2d_Kohonen_maps
Fuzzy c-means clustering of histogram data with adaptive distancesWH_adaptive_fcmeans
K-means clustering of histogram data with adaptive distancesWH_adaptive.kmeans
Fuzzy c-means clustering of histogram dataWH_fcmeans
Hierarchical clustering of histogram dataWH_hclust
K-means clustering of histogram dataWH_kmeans
L2 Wasserstein distance matrixWH_MAT_DIST
Principal component analysis of a histogram variableWH.1d.PCA
Bind matrices of histogramsWH.bind WH.bind,MatH,MatH-method WH.bind,MatH-method WH.bind.col WH.bind.col,MatH,MatH-method WH.bind.col,MatH-method WH.bind.row WH.bind.row,MatH,MatH-method WH.bind.row,MatH-method
Product of two matrices of histogramsWH.mat.prod WH.mat.prod,MatH,MatH-method WH.mat.prod,MatH-method
Sum of two matrices of histogramsWH.mat.sum WH.mat.sum,MatH,MatH-method WH.mat.sum,MatH-method
Principal component analysis of a set of histogram variablesWH.MultiplePCA
Plot the histograms of the individuals on a factorial planeWH.plot_multiple_indivs
Plot the variables of a PCA of histogram variables (Spanish-fan plot)WH.plot_multiple_Spanish.funs
Goodness of fit of a two-component regression of histogram variablesWH.regression.GOF
Two-component regression of histogram variablesWH.regression.two.components
Predictions of a two-component regression of histogram variablesWH.regression.two.components.predict
Sum of squares, covariance and correlation of histogram variablesWH.correlation WH.correlation,MatH-method WH.correlation2 WH.correlation2,MatH,MatH-method WH.correlation2,MatH-method WH.SSQ WH.SSQ,MatH-method WH.SSQ2 WH.SSQ2,MatH,MatH-method WH.SSQ2,MatH-method WH.var.covar WH.var.covar,MatH-method WH.var.covar2 WH.var.covar2,MatH,MatH-method WH.var.covar2,MatH-method
Weighted sum and mean of the histograms of a matrixWH.vec.mean WH.vec.mean,MatH-method WH.vec.sum WH.vec.sum,MatH-method