rnorm_mix: Random Generator of a Normal Mixture

In matheuscastro43/mixGM: Finite Mixture Models

Description

Generates random samples of a univariate Normal mixture.

Usage

 rnorm_mix(n, pi, mean, sd, plot.it = TRUE, empirical = FALSE, col.pop = "red3",
           col.empirical = "navy", ...)

Arguments

n	number of observations.
pi	vector of mixture weights.
mean	vector of mixture means.
sd	vector of mixture standard desviations.
plot.it	logical, TRUE to plot the histogram with estimated distribution curve.
empirical	logical, TRUE to add the empirical curve ("Kernel Density Estimation") in the plot.
col.pop	a colour to be used in the curve of population density.
col.empirical	a colour to be used in the curve of empirical density.
...	further arguments and graphical parameters passed to hist.

Author(s)

CASTRO, M. O.; MONTALVO, G. S. A.

Examples

## Generate a sample.
data = rnorm_mix(n = 1000, pi = c(0.6, 0.4), mean = c(10, 18), sd = c(1, 2))

## Sample vector.
data$sample
## The classification of each observation.
data$classification
## The histogram of the sample with population density curve.
data$plot

## Not plotting the graphic.
rnorm_mix(n = 1000, pi = c(0.6, 0.4), mean = c(10, 18), sd = c(1, 2), plot.it = FALSE)

## Adding the empirical curve to the graphic.
rnorm_mix(n = 1000, pi = c(0.6, 0.4), mean = c(10, 18), sd = c(1, 2), plot.it = TRUE,
          empirical = TRUE)

## Changing the color of the curves.
rnorm_mix(n = 1000, pi = c(0.6, 0.4), mean = c(10, 18), sd = c(1, 2), plot.it = TRUE,
          empirical = TRUE, col.pop = "blue", col.empirical = "green")

## Using "...".
rnorm_mix(n = 1000, pi = c(0.6, 0.4), mean = c(10, 18), sd = c(1, 2), breaks = 300)

matheuscastro43/mixGM documentation built on March 2, 2020, 12:19 a.m.