dmvtmix: Density of the Multivariate t Mixture Distribution with...
In RGLab/flowClust: Clustering for Flow Cytometry

dmvtmix

R Documentation

Density of the Multivariate t Mixture Distribution with Box-Cox Tranformation

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

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

`x`	A matrix or data frame of size `N \times 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 \times P` containing the `K` mean vectors.
`sigma`	An array of size `K \times P \times 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.