Statistical Methods for Anthropometric Data
Helper generic function for obtaining the anthropometric cases
Several internal functions to compute and represent archetypes and arc...
Several internal functions used by both and alg...
Several internal functions used to build the HIPAM plot tree
Several internal functions to clustering based on the L1 data depth
Statistical Methods for Anthropometric Data
Archetypal analysis in multivariate accommodation problem
Finding archetypoids
Helper function for the 3D landmarks
Helper function for defining the bust sizes
Cheng and Church biclustering algorithm applied to anthropometric data
CDF for the dissimilarities between women and computed medoids and sta...
Evaluation of the candidate clustering partition in
Evaluation of the candidate clustering partition in
Computation of the hipamAnthropom elements for a given number of sizes...
Computation of the trimowa elements for a given number of sizes define...
Figures of 8 landmarks with labelled landmarks
Generation of the candidate clustering partition in
Generation of the candidate clustering partition in
Dissimilarity matrix between individuals and prototypes
Hartigan-Wong k-means for 3D shapes
HIPAM algorithm for anthropometric data
Lloyd k-means for 3D shapes
Nearest individuals to archetypes
Auxiliary optra subroutine of the Hartigan-Wong k-means for 3D shapes
Overlapped biclusters by rows
Helper function for computing percentiles of a certain archetypoid
Prototypes representation
HIPAM dendogram
Trimmed or outlier observations representation
Data preprocessing before computing archetypal observations
Helper function for plotting the shapes
Auxiliary qtran subroutine of the Hartigan-Wong k-means for 3D shapes
Screeplot of archetypal individuals
3D shapes plot
Skeleton plot of archetypal individuals
Archetype algorithm to raw data
Run the archetypoid algorithm several times
Trimmed clustering based on L1 data depth
Trimmed Lloyd k-means for 3D shapes
Trimmed k-medoids algorithm
Helper generic function for obtaining the trimmed and outlier observat...
Trimmed PAM with OWA operators
Calculation of the weights for the OWA operators
PC scores for archetypes
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>.
Useful links