% Generated by roxygen2: do not edit by hand % Please edit documentation in R/hca_class.R \name{HCA} \alias{HCA} \title{Hierarchical Cluster Analysis} \usage{ HCA( dist_method = "euclidean", cluster_method = "complete", minkowski_power = 2, factor_name, ... ) } \arguments{ \item{dist_method}{(character) Distance measure. Allowed values are limited to the following: \itemize{ \item{\code{"euclidean"}: The euclidean distance (2 norm).}\item{\code{"maximum"}: The maximum distance.}\item{\code{"manhattan"}: The absolute distance (1 norm).}\item{\code{"canberra"}: A weighted version of the mahattan distance.}\item{\code{"minkowski"}: A generalisation of manhattan and euclidean distance to nth norm.}} The default is \code{"euclidean"}.} \item{cluster_method}{(character) Agglomeration method. Allowed values are limited to the following: \itemize{ \item{\code{"ward.D"}: Ward clustering.}\item{\code{"ward.D2"}: Ward clustering using sqaured distances.}\item{\code{"single"}: Single linkage.}\item{\code{"complete"}: Complete linkage.}\item{\code{"average"}: Average linkage (UPGMA).}\item{\code{"mcquitty"}: McQuitty linkage (WPGMA).}\item{\code{"median"}: Median linkage (WPGMC).}\item{\code{"centroid"}: Centroid linkage (UPGMC).}} The default is \code{"complete"}.} \item{minkowski_power}{(numeric) The default is \code{2}.\cr} \item{factor_name}{(character) The name of a sample-meta column to use.} \item{...}{Additional slots and values passed to \code{struct_class}.} } \value{ A \code{HCA} object with the following \code{output} slots: \tabular{ll}{ \code{dist_matrix} \tab (dist) An object containing pairwise distance information between samples. \cr \code{hclust} \tab (hclust) An object of class hclust which describes the tree produced by the clustering process. \cr \code{factor_df} \tab (data.frame) \cr } } \description{ Hierarchical Cluster Analysis is a numerical technique that uses agglomerative clustering to identify clusters or groupings of samples. } \details{ This object makes use of functionality from the following packages:\itemize{ \item{\code{stats}}} } \section{Inheritance}{ A \code{HCA} object inherits the following \code{struct} classes: \cr\cr \verb{[HCA]} >> \verb{[model]} >> \verb{[struct_class]} } \examples{ M = HCA( dist_method = "euclidean", cluster_method = "complete", minkowski_power = numeric(0), factor_name = "V1") D = iris_DatasetExperiment() M = HCA(factor_name='Species') M = model_apply(M,D) } \references{ R Core Team (2024). \emph{R: A Language and Environment for Statistical Computing}. R Foundation for Statistical Computing, Vienna, Austria. \url{https://www.R-project.org/}. }