egamma: Gamma Distribution Estimation

In matheuscastro43/finiteMix: Finite Mixture Models

Gamma Distribution Estimation

Description

Estimates parameters of a univariate Gamma Distribution with maximum likelihood.

Usage

egamma(data, plot.it = TRUE, empirical = FALSE, col.estimated = "orange",
       col.empirical = "navy", ...)

Arguments

data	vector containing the sample as rgamma.
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.estimated	a colour to be used in the curve of estimated 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 = rgamma(n = 1000, shape = 18, scale = 2)

## And now, estimate the parameters, using the 'data' list.
egamma(data)

## Not plotting the graphic.
egamma(data, plot.it = FALSE)

## Adding the empirical curve to the graphic.
egamma(data, empirical = TRUE)

## Changing the color of the curves.
egamma(data, empirical = TRUE, col.estimated = "pink", 
          col.empirical = "red3")

## Using "..."
egamma(data, empirical = TRUE, col.estimated = "pink", 
       col.empirical = "red3", breaks = 300)

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