movMF_reduce_partitional: von Mises-Fisher mixture model reduction - partitional method
In maotai: Tools for Matrix Algebra, Optimization and Inference

movMF_reduce_partitional

R Documentation

von Mises-Fisher mixture model reduction - partitional method

When given parameters of the von Mises-Fisher mixture model, this function aims at mixture model reduction using a partitional method.

movMF_reduce_partitional(
  means,
  concentrations,
  weights,
  target.num = 2,
  method = c("hclust", "kmedoids")
)

`means`	a `(K \times p)` matrix of means of the von Mises-Fisher components.
`concentrations`	a `K` vector of concentrations of the von Mises-Fisher components.
`weights`	a `K` vector of weights of the von Mises-Fisher components.
`target.num`	a desired number of components after reduction. Default is 2.
`method`	a clustering method to be used. Default is "hclust".

a named list of the reduced mixture model containing

means: a (\code{target.num} \times p) matrix of means of the von Mises-Fisher components.
concentrations: a \code{target.num} vector of concentrations of the von Mises-Fisher components.
weights: a \code{target.num} vector of weights of the von Mises-Fisher components.