Package: Anthropometry 1.19

Guillermo Vinue

Anthropometry: Statistical Methods for Anthropometric Data

Statistical methodologies especially developed to analyze anthropometric data. These methods are aimed at providing effective solutions to some commons problems related to Ergonomics and Anthropometry. They are based on clustering, the statistical concept of data depth, statistical shape analysis and archetypal analysis. Please see Vinue (2017) <doi:10.18637/jss.v077.i06>.

Authors:Guillermo Vinue, Irene Epifanio, Amelia Simo, M. Victoria Ibanez, Juan Domingo, Guillermo Ayala

Anthropometry_1.19.tar.gz
Anthropometry_1.19.tar.gz(r-4.5-noble)Anthropometry_1.19.tar.gz(r-4.4-noble)
Anthropometry_1.19.tgz(r-4.4-emscripten)Anthropometry_1.19.tgz(r-4.3-emscripten)
Anthropometry.pdf |Anthropometry.html✨
Anthropometry/json (API)
NEWS

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.78 score 1 stars 2 packages 862 downloads 40 exports 85 dependencies

Last updated 2 years agofrom:d7cdec4461. Checks:1 OK, 1 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 28 2025
R-4.5-linux-x86_64NOTEFeb 28 2025

Exports:anthrCasesarchetypesBoundaryarchetypoidsarray3DlandmbustSizesStandardCCbiclustAnthropocdfDissWomenPrototypescheckBranchLocalIMOcheckBranchLocalMOcomputSizesHipamAnthropomcomputSizesTrimowafigures8landmgetBestPamsamIMOgetBestPamsamMOgetDistMatrixHartiganShapeshipamAnthropomLloydShapesnearestToArchetypesoptraShapesoverlapBiclustersByRowspercentilsArchetypoidplotPrototypesplotTreeHipamAnthropomplotTrimmOutlpreprocessingprojShapesqtranShapesscreeArchetypalshapes3dShapesskeletonsArchetypalstepArchetypesRawDatastepArchetypoidsTDDclusttrimmedLloydShapestrimmedoidtrimmOutltrimowaweightsMixtureUBxyplotPCArchetypes

Dependencies:abindadditivityTestsarchetypesbase64encBHbiclustbslibcachemclasscliclustercolorspacecpp11ddalphaDEoptimRdigestdplyrevaluatefansifarverfastclusterfastmapflexclustFNNfontawesomefsgenericsgeometryggplot2gluegtablehighrhtmltoolshtmlwidgetsICGEisobandjquerylibjsonliteknitrlabelinglatticelifecyclelinproglpSolvemagicmagrittrMASSMatrixmemoisemgcvmimeminpack.lmmodeltoolsmunsellnlmennlspillarpkgconfigpurrrR6rappdirsRColorBrewerRcppRcppProgressrglrlangrmarkdownrobustbasesassscalesscatterplot3dsfsmiscshapesstringistringrtibbletidyrtidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Developing statistical methodologies for Anthropometry

Rendered fromAnthropometry.Rnwusingknitr::knitron Feb 28 2025.

Last update: 2019-04-29
Started: 2014-03-07

Readme and manuals

Help Manual

Help pageTopics
Statistical Methods for Anthropometric DataAnthropometry-package
Helper generic function for obtaining the anthropometric casesanthrCases anthrCases.default anthrCases.hipamAnthropom anthrCases.trimowa
Archetypal analysis in multivariate accommodation problemarchetypesBoundary
Finding archetypoidsarchetypoids
Helper function for the 3D landmarksarray3Dlandm
Helper function for defining the bust sizesbustSizesStandard
Cheng and Church biclustering algorithm applied to anthropometric dataCCbiclustAnthropo
CDF for the dissimilarities between women and computed medoids and standard prototypescdfDissWomenPrototypes
Evaluation of the candidate clustering partition in $HIPAM_IMO$checkBranchLocalIMO
Evaluation of the candidate clustering partition in $HIPAM_MO$checkBranchLocalMO
Computation of the hipamAnthropom elements for a given number of sizes defined by the ENcomputSizesHipamAnthropom
Computation of the trimowa elements for a given number of sizes defined by the ENcomputSizesTrimowa
Cube of 34 landmarkscube34landm
Cube of 8 landmarkscube8landm
Description of the dissimilarities between women's trunksdescrDissTrunks
Figures of 8 landmarks with labelled landmarksfigures8landm
Generation of the candidate clustering partition in $HIPAM_IMO$getBestPamsamIMO
Generation of the candidate clustering partition in $HIPAM_MO$getBestPamsamMO
Dissimilarity matrix between individuals and prototypesgetDistMatrix
Hartigan-Wong k-means for 3D shapesHartiganShapes
HIPAM algorithm for anthropometric datahipamAnthropom
Landmarks of the sampled women of the Spanish SurveylandmarksSampleSpaSurv
Lloyd k-means for 3D shapesLloydShapes
Nearest individuals to archetypesnearestToArchetypes
Auxiliary optra subroutine of the Hartigan-Wong k-means for 3D shapesoptraShapes
Overlapped biclusters by rowsoverlapBiclustersByRows
Parallelepiped of 34 landmarksparallelep34landm
Parallelepiped of 8 landmarksparallelep8landm
Helper function for computing percentiles of a certain archetypoidpercentilsArchetypoid
Prototypes representationplotPrototypes
HIPAM dendogramplotTreeHipamAnthropom
Trimmed or outlier observations representationplotTrimmOutl
Data preprocessing before computing archetypal observationspreprocessing
Helper function for plotting the shapesprojShapes
Auxiliary qtran subroutine of the Hartigan-Wong k-means for 3D shapesqtranShapes
Sample database of the Spanish anthropometric surveysampleSpanishSurvey
Screeplot of archetypal individualsscreeArchetypal
3D shapes plotshapes3dShapes
Skeleton plot of archetypal individualsskeletonsArchetypal
Archetype algorithm to raw datastepArchetypesRawData
Run the archetypoid algorithm several timesstepArchetypoids
Trimmed clustering based on L1 data depthTDDclust
Trimmed Lloyd k-means for 3D shapestrimmedLloydShapes
Trimmed k-medoids algorithmtrimmedoid
Helper generic function for obtaining the trimmed and outlier observationstrimmOutl trimmOutl.default trimmOutl.hipamAnthropom trimmOutl.trimowa
Trimmed PAM with OWA operatorstrimowa
USAF 1967 surveyUSAFSurvey
Calculation of the weights for the OWA operatorsweightsMixtureUB
PC scores for archetypesxyplotPCArchetypes