plot.univariateML: Plot, Lines and Points Methods for Maximum Likelihood...

In univariateML: Maximum Likelihood Estimation for Univariate Densities

Plot, Lines and Points Methods for Maximum Likelihood Estimates

Description

The plot, lines, and points methods for univariateML objects.

Usage

## S3 method for class 'univariateML'
plot(x, range = NULL, kind = c("d", "p", "q"), ...)

## S3 method for class 'univariateML'
lines(x, range = NULL, kind = c("d", "p", "q"), ...)

## S3 method for class 'univariateML'
points(x, range = NULL, kind = c("d", "p", "q"), ...)

Arguments

x	a univariateML object.
range	range of x values to plot, i.e. c(lower, upper).
kind	can be density, probability, or quantile.
...	parameters passed to plot, lines, or points.

Value

An invisible copy of x.

Examples

plot(mlweibull(datasets::precip), main = "Annual Precipitation in US Cities")
lines(mlgamma(datasets::precip), lty = 2)
rug(datasets::precip)

univariateML documentation built on April 3, 2025, 11:09 p.m.