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Anthropometry (version 1.19)

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) .

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Version

Install

install.packages('Anthropometry')

Monthly Downloads

593

Version

1.19

License

GPL (>= 2)

Homepage

https://www.R-project.org

Maintainer

Guillermo Vinue

Last Published

February 22nd, 2023

Functions in Anthropometry (1.19)

CCbiclustAnthropo

Cheng and Church biclustering algorithm applied to anthropometric data

cdfDissWomenPrototypes

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

bustSizesStandard

Helper function for defining the bust sizes

Finding archetypoids

Helper function for the 3D landmarks

Anthropometry-internalArchetypoids

Several internal functions to compute and represent archetypes and archetypoids

Anthropometry-internalHipamAnthropom

Several internal functions used by both $HIPAM_MO$ and $HIPAM_IMO$ algorithms

Helper generic function for obtaining the anthropometric cases

checkBranchLocalMO

Evaluation of the candidate clustering partition in $HIPAM_MO$

landmarksSampleSpaSurv

Landmarks of the sampled women of the Spanish Survey

checkBranchLocalIMO

Evaluation of the candidate clustering partition in $HIPAM_IMO$

Dissimilarity matrix between individuals and prototypes

archetypesBoundary

Archetypal analysis in multivariate accommodation problem

getBestPamsamIMO

Generation of the candidate clustering partition in $HIPAM_IMO$

HIPAM algorithm for anthropometric data

Figures of 8 landmarks with labelled landmarks

descrDissTrunks

Description of the dissimilarities between women's trunks

overlapBiclustersByRows

Overlapped biclusters by rows

parallelep34landm

Parallelepiped of 34 landmarks

nearestToArchetypes

Nearest individuals to archetypes

parallelep8landm

Parallelepiped of 8 landmarks

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

computSizesHipamAnthropom

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

Cube of 34 landmarks

Helper function for plotting the shapes

Data preprocessing before computing archetypal observations

computSizesTrimowa

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

Cube of 8 landmarks

percentilsArchetypoid

Helper function for computing percentiles of a certain archetypoid

skeletonsArchetypal

Skeleton plot of archetypal individuals

Prototypes representation

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

getBestPamsamMO

Generation of the candidate clustering partition in $HIPAM_MO$

plotTreeHipamAnthropom

HIPAM dendogram

screeArchetypal

Screeplot of archetypal individuals

stepArchetypoids

Run the archetypoid algorithm several times

xyplotPCArchetypes

PC scores for archetypes

Helper generic function for obtaining the trimmed and outlier observations

Trimmed or outlier observations representation

trimmedLloydShapes

Trimmed Lloyd k-means for 3D shapes

Trimmed k-medoids algorithm

stepArchetypesRawData

Archetype algorithm to raw data

sampleSpanishSurvey

Sample database of the Spanish anthropometric survey

Trimmed PAM with OWA operators

weightsMixtureUB

Calculation of the weights for the OWA operators

USAF 1967 survey

Anthropometry-internalPlotTree

Several internal functions used to build the HIPAM plot tree

Anthropometry-package

Statistical Methods for Anthropometric Data

Lloyd k-means for 3D shapes

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