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Anthropometry (version 1.13)

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

660

Version

1.13

License

GPL (>= 2)

Homepage

https://www.R-project.org

Maintainer

Guillermo Vinue

Last Published

December 6th, 2019

Functions in Anthropometry (1.13)

Anthropometry-internalArchetypoids

Several internal functions to compute and represent archetypes and archetypoids

computSizesTrimowa

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

USAF 1967 survey

Trimmed clustering based on L1 data depth

computSizesHipamAnthropom

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

Cube of 34 landmarks

checkBranchLocalIMO

Evaluation of the candidate clustering partition in $HIPAM_IMO$

Anthropometry-internalHipamAnthropom

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

Dissimilarity matrix between individuals and prototypes

checkBranchLocalMO

Evaluation of the candidate clustering partition in $HIPAM_MO$

Anthropometry-internalPlotTree

Several internal functions used to build the HIPAM plot tree

HIPAM algorithm for anthropometric data

Anthropometry-internalTDDclust

Several internal functions to clustering based on the L1 data depth

Cube of 8 landmarks

bustSizesStandard

Helper function for defining the bust sizes

Helper generic function for obtaining the anthropometric cases

descrDissTrunks

Description of the dissimilarities between women's trunks

Figures of 8 landmarks with labelled landmarks

archetypesBoundary

Archetypal analysis in multivariate accommodation problem

Finding archetypoids

Helper function for the 3D landmarks

Lloyd k-means for 3D shapes

Hartigan-Wong k-means for 3D shapes

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

overlapBiclustersByRows

Overlapped biclusters by rows

nearestToArchetypes

Nearest individuals to archetypes

landmarksSampleSpaSurv

Landmarks of the sampled women of the Spanish Survey

parallelep8landm

Parallelepiped of 8 landmarks

parallelep34landm

Parallelepiped of 34 landmarks

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

Trimmed or outlier observations representation

plotTreeHipamAnthropom

HIPAM dendogram

skeletonsArchetypal

Skeleton plot of archetypal individuals

stepArchetypesRawData

Archetype algorithm to raw data

cdfDissWomenPrototypes

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

percentilsArchetypoid

Helper function for computing percentiles of a certain archetypoid

screeArchetypal

Screeplot of archetypal individuals

xyplotPCArchetypes

PC scores for archetypes

stepArchetypoids

Run the archetypoid algorithm several times

Helper generic function for obtaining the trimmed and outlier observations

getBestPamsamIMO

Generation of the candidate clustering partition in $HIPAM_IMO$

getBestPamsamMO

Generation of the candidate clustering partition in $HIPAM_MO$

Helper function for plotting the shapes

Data preprocessing before computing archetypal observations

sampleSpanishSurvey

Sample database of the Spanish anthropometric survey

Trimmed PAM with OWA operators

weightsMixtureUB

Calculation of the weights for the OWA operators

trimmedLloydShapes

Trimmed Lloyd k-means for 3D shapes

Prototypes representation

Trimmed k-medoids algorithm

CCbiclustAnthropo

Cheng and Church biclustering algorithm applied to anthropometric data

Anthropometry-package

Statistical Methods for Anthropometric Data