dmvtmix: Density of the Multivariate t Mixture Distribution with...

In flowClust: Clustering for Flow Cytometry

Description

This function computes the densities at the inputted points of the multivariate t mixture distribution with Box-Cox transformation.

Usage

dmvtmix(x, w, mu, sigma, nu, lambda, object, subset, include,
  log = FALSE)

Arguments

x	A matrix or data frame of size N x P, where N is the number of observations and P is the dimension. Each row corresponds to one observation.
w	A numeric vector of length K containing the cluster proportions.
mu	A matrix of size K x P containing the K mean vectors.
sigma	An array of size K x P x P containing the K covariance matrices.
nu	A numeric vector of length K containing the degrees of freedom used for the t distribution. If only one value is specified for nu, then it is used for all K clusters. If nu=Inf, Gaussian distribution will be used.
lambda	The Box-Cox transformation parameter. If missing, the conventional t distribution without transformation will be used.
object	An optional argument. If provided, it's an object returned from flowClust, and the previous arguments will be assigned values from the corresponding slots of object.
subset	An optional argument. If provided, it's a numeric vector indicating which variables are selected for computing the densities. If object is provided and object@varNames is not NULL, then a character vector containing the names of the variables is allowed.
include	An optional argument. If provided, it's a numeric vector specifying which clusters are included for computing the densities.
log	A logical value. If TRUE then the logarithm of the densities is returned.

Value

A vector of length N containing the density values.

Author(s)

Raphael Gottardo <[e-mail]>, Kenneth Lo <[e-mail]>

flowClust documentation built on Nov. 8, 2020, 7:34 p.m.