Archetypal analysis in multivariate accommodation problem
Cube of 34 landmarks
Description of the dissimilarities between women's trunks
Figures of 8 landmarks with labelled landmarks
Helper function for computing percentiles of a certain archetypoid
Dissimilarity matrix between individuals and prototypes
Prototypes representation
Screeplot of archetypal individuals
3D shapes plot
Trimmed or outlier observations representation
HIPAM dendogram
HIPAM algorithm for anthropometric data
Skeleton plot of archetypal individuals
Auxiliary optra subroutine of the Hartigan-Wong k-means for 3D shapes
Overlapped biclusters by rows
Archetype algorithm to raw data
Cube of 8 landmarks
Parallelepiped of 34 landmarks
Landmarks of the sampled women of the Spanish Survey
Nearest individuals to archetypes
CDF for the dissimilarities between women and computed medoids and standard prototypes
Generation of the candidate clustering partition in $HIPAM_IMO$
Helper generic function for obtaining the trimmed and outlier observations
Run the archetypoid algorithm several times
Auxiliary qtran subroutine of the Hartigan-Wong k-means for 3D shapes
Generation of the candidate clustering partition in $HIPAM_MO$
Parallelepiped of 8 landmarks
Trimmed Lloyd k-means for 3D shapes
Calculation of the weights for the OWA operators
Data preprocessing before computing archetypal observations
Trimmed k-medoids algorithm
Helper function for plotting the shapes
Trimmed PAM with OWA operators
Sample database of the Spanish anthropometric survey
PC scores for archetypes
Statistical Methods for Anthropometric Data
Trimmed clustering based on L1 data depth
Anthropometry-internalHipamAnthropom
Several internal functions used by both $HIPAM_MO$ and $HIPAM_IMO$ algorithms
Lloyd k-means for 3D shapes
Anthropometry-internalPlotTree
Several internal functions used to build the HIPAM plot tree
Anthropometry-internalArchetypoids
Several internal functions to compute and represent archetypes and archetypoids
USAF 1967 survey
Hartigan-Wong k-means for 3D shapes
Anthropometry-internalTDDclust
Several internal functions to clustering based on the L1 data depth
Cheng and Church biclustering algorithm applied to anthropometric data
Evaluation of the candidate clustering partition in $HIPAM_MO$
Helper function for the 3D landmarks
Helper function for defining the bust sizes
Helper generic function for obtaining the anthropometric cases
Evaluation of the candidate clustering partition in $HIPAM_IMO$
Computation of the trimowa elements for a given number of sizes defined by the EN
computSizesHipamAnthropom
Computation of the hipamAnthropom elements for a given number of sizes defined by the EN
Finding archetypoids