rcnorm: Random Generator of a Contaminated Normal Distribution

In matheuscastro43/finiteMix: Finite Mixture Models

Random Generator of a Contaminated Normal Distribution

Description

Generates random samples of a univariate Contaminated Normal Distribution.

Usage

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

Arguments

n	number of observations.
pi	vector of mixture weights.
mean	value of mixture mean.
sd	value of standard deviation parameter.
gamma	value of gamma parameter.
plot.it	logical; if TRUE (default), plot the histogram with estimated distribution curve.
empirical	logical; if TRUE, 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 = rcnorm(n = 1000, pi = c(0.6, 0.4), mean = 10, sd = 1, gamma = 3)

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

## Not plotting the graphic.
rcnorm(n = 1000, pi = c(0.6, 0.4), mean = 10, sd = 1, gamma = 3, plot.it = FALSE)

## Adding the empirical curve to the graphic.
rcnorm(n = 1000, pi = c(0.6, 0.4), mean = 10, sd = 1, gamma = 3, plot.it = TRUE,
          empirical = TRUE)

## Changing the color of the curves.
rcnorm(n = 1000, pi = c(0.6, 0.4), mean = 10, sd = 1, gamma = 3, plot.it = TRUE,
          empirical = TRUE, col.pop = "blue", col.empirical = "green")

## Using "...".
rcnorm(n = 1000, pi = c(0.6, 0.4), mean = 10, sd = 1, gamma = 3, breaks = 300)

matheuscastro43/finiteMix documentation built on March 30, 2022, 12:49 p.m.