SimulateMixture {flowClust} | R Documentation |
This function can be used to generate a sample from a multivariate t mixture model.
SimulateMixture(N, nu=100, mu, sigma, w)
N |
The number of observations. |
nu |
The degrees of freedom used for the t distribution. |
mu |
A matrix of size K x P, where K is the number of clusters and P is the dimension, containing the K mean vectors. |
sigma |
An array of dimension K x P x P, containing the K covariance matrices. |
w |
A vector of length K, containing the K cluster proportions. |
A matrix of size N x P.
Raphael Gottardo <raph@stat.ubc.ca>, Kenneth Lo <c.lo@stat.ubc.ca>
### Number of components K <- 5 ### Dimension p <- 2 ### Number of observations n <- 200 Mu <- matrix(runif(K*p, 0, 20), K, p) Sigma <- array(0, c(K, p, p)) for (k in 1:K) { Sigma[k,,][outer(1:p, 1:p, ">")] <- runif(p*(p-1)/2,-.1,.1) diag(Sigma[k,,]) <- runif(p,0,1) ### Make sigma positive definite Sigma[k,,] <- Sigma[k,,] %*% t(Sigma[k,,]) } ### Generate the weights w <- rgamma(K,10,1) w <- w/sum(w) y <- SimulateMixture(n, nu=4, Mu, Sigma, w)