Learn R Programming

Anthropometry (version 1.21)

Statistical Methods for Anthropometric Data

Description

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) .

Copy Link

Version

Install

install.packages('Anthropometry')

Monthly Downloads

385

Version

1.21

License

GPL (>= 2)

Homepage

https://www.R-project.org

Maintainer

Guillermo Vinue

Last Published

December 4th, 2025

Functions in Anthropometry (1.21)

Dissimilarity matrix between individuals and prototypes

nearestToArchetypes

Nearest individuals to archetypes

descrDissTrunks

Description of the dissimilarities between women's trunks

getBestPamsamIMO

Generation of the candidate clustering partition in HIPAM-IMO

HIPAM algorithm for anthropometric data

landmarksSampleSpaSurv

Landmarks of the sampled women of the Spanish Survey

Cube of 8 landmarks

Figures of 8 landmarks with labelled landmarks

checkBranchLocalMO

Evaluation of the candidate clustering partition in HIPAM-MO

Auxiliary optra subroutine of the Hartigan-Wong k-means for 3D shapes

getBestPamsamMO

Generation of the candidate clustering partition in HIPAM-MO

percentilsArchetypoid

Helper function for computing percentiles of a certain archetypoid

Auxiliary qtran subroutine of the Hartigan-Wong k-means for 3D shapes

parallelep8landm

Parallelepiped of 8 landmarks

Prototypes representation

parallelep34landm

Parallelepiped of 34 landmarks

sampleSpanishSurvey

Sample database of the Spanish anthropometric survey

Helper function for plotting the shapes

Data preprocessing before computing archetypal observations

Trimmed or outlier observations representation

plotTreeHipamAnthropom

HIPAM dendogram

trimmedLloydShapes

Trimmed Lloyd k-means for 3D shapes

weightsMixtureUB

Calculation of the weights for the OWA operators

Trimmed k-medoids algorithm

skeletonsArchetypal

Skeleton plot of archetypal individuals

stepArchetypoids

Run the archetypoid algorithm several times

xyplotPCArchetypes

PC scores for archetypes

stepArchetypesRawData

Archetype algorithm to raw data

Trimmed PAM with OWA operators

Helper generic function for obtaining the trimmed and outlier observations

screeArchetypal

Screeplot of archetypal individuals

Anthropometry-internalArchetypoids

Several internal functions to compute and represent archetypes and archetypoids

Anthropometry-internalPlotTree

Several internal functions used to build the HIPAM plot tree

Anthropometry-internalHipamAnthropom

Several internal functions used by both HIPAM-MO and HIPAM-IMO algorithms

Anthropometry-package

Statistical Methods for Anthropometric Data

Lloyd k-means for 3D shapes

Helper generic function for obtaining the anthropometric cases

Anthropometry-internalTDDclust

Several internal functions to clustering based on the L1 data depth

Trimmed clustering based on L1 data depth

Hartigan-Wong k-means for 3D shapes

USAF 1967 survey

Helper function for the 3D landmarks

computSizesHipamAnthropom

Computation of the hipamAnthropom elements for a given number of sizes defined by the EN

Cube of 34 landmarks

bustSizesStandard

Helper function for defining the bust sizes

computSizesTrimowa

Computation of the trimowa elements for a given number of sizes defined by the EN

archetypesBoundary

Archetypal analysis in multivariate accommodation problem

Finding archetypoids

cdfDissWomenPrototypes

CDF for the dissimilarities between women and computed medoids and standard prototypes

checkBranchLocalIMO

Evaluation of the candidate clustering partition in HIPAM-IMO