rnormmix: Generate Random Samples from a Normal Mixture Model

In mritc: MRI Tissue Classification

Generate Random Samples from a Normal Mixture Model

Description

Generate random samples from a normal mixture model.

Usage

   rnormmix(n, prop, mu, sigma)

Arguments

n	number of observations.
prop	a vector of proportions of different components.
mu	a vector of means of different components.
sigma	a vector of standard deviations of different components

Value

A matrix with each row corresponding to one sample. The first column are sample values from a normal mixture model; the second column are the components from which observations come.

Examples

  prop <- c(.17, .48, .35)
  mu <- c(-4, 0, 4)
  sigma <- rep(1, 3)
  y <- rnormmix(n=10000, prop, mu, sigma)
  densityplot(~ y[,1], groups = y[,2],
              plot.points = FALSE, ref = TRUE,
              xlab="sample values",
              auto.key = list(columns = 3))

mritc documentation built on Feb. 16, 2023, 10:47 p.m.