| Random Normal Mixture | R Documentation |
Generates random samples of a univariate Normal Mixture.
rnorm_mix(n, pi, mean, sd, plot.it = TRUE, empirical = FALSE, col.pop = "red3",
col.empirical = "navy", ...)
n |
number of observations. |
pi |
vector of mixture weights. |
mean |
vector of mixture means. |
sd |
vector of mixture standard deviations. |
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. |
CASTRO, M. O.; MONTALVO, G. S. A.
## 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)
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