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Anthropometry (version 1.7)

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.

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Version

Install

install.packages('Anthropometry')

Monthly Downloads

487

Version

1.7

License

GPL (>= 2)

Homepage

http://www.r-project.org

Maintainer

Guillermo Vinue

Last Published

December 12th, 2015

Functions in Anthropometry (1.7)

Helper function for the 3D landmarks

Lloyd k-means for 3D shapes

Anthropometry-internalArchetypoids

Several internal functions to compute and represent archetypes and archetypoids

cdfDissWomenPrototypes

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

Anthropometry-internalTDDclust

Several internal functions to clustering based on the L1 data depth

USAF 1967 survey

Helper generic function for obtaining the anthropometric cases

Figures of 8 landmarks with labelled landmarks

CCbiclustAnthropo

Cheng and Church biclustering algorithm applied to anthropometric data

computSizesHipamAnthropom

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

computSizesTrimowa

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

landmarksSampleSpaSurv

Landmarks of the sampled women of the Spanish Survey

screeArchetypal

Screeplot of archetypal individuals

Helper function for plotting the shapes

getBestPamsamMO

Generation of the candidate clustering partition in $HIPAM_MO$

parallelep8landm

Parallelepiped of 8 landmarks

plotTreeHipamAnthropom

HIPAM dendogram

overlapBiclustersByRows

Overlapped biclusters by rows

Hartigan-Wong k-means for 3D shapes

Helper function for the percentils of the archetypoids

nearestToArchetypes

Nearest individuals to archetypes

Anthropometry-internalHipamAnthropom

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

percentilsArchetypoid

Computing percentiles of a certain archetypoid

Cube of 8 landmarks

stepArchetypesRawData

Archetype algorithm to raw data

sampleSpanishSurvey

Sample database of the Spanish anthropometric survey

Trimmed k-medoids algorithm

Trimmed or outlier observations representation

archetypesBoundary

Archetypal analysis in multivariate accommodation problem

checkBranchLocalIMO

Evaluation of the candidate clustering partition in $HIPAM_IMO$

Helper generic function for obtaining the trimmed and outlier observations

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

bustSizesStandard

Helper function for defining the bust sizes

checkBranchLocalMO

Evaluation of the candidate clustering partition in $HIPAM_MO$

Data preprocessing before computing archetypal observations

Dissimilarity matrix between individuals and prototypes

Anthropometry-internalPlotTree

Several internal functions used to build the HIPAM plot tree

descrDissTrunks

Description of the dissimilarities between women's trunks

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

Trimmed PAM with OWA operators

xyplotPCArchetypes

PC scores for archetypes

parallelep34landm

Parallelepiped of 34 landmarks

stepArchetypoids

Run the archetypoid algorithm several times

weightsMixtureUB

Calculation of the weights for the OWA operators

getBestPamsamIMO

Generation of the candidate clustering partition in $HIPAM_IMO$

trimmedLloydShapes

Trimmed Lloyd k-means for 3D shapes

Trimmed clustering based on L1 data depth

Prototypes representation

Anthropometry-package

Statistical Methods for Anthropometric Data

skeletonsArchetypal

Skeleton plot of archetypal individuals

Finding archetypoids

Cube of 34 landmarks

HIPAM algorithm for anthropometric data