mlrayleigh: Rayleigh distribution maximum likelihood estimation

In univariateML: Maximum Likelihood Estimation for Univariate Densities

Description

Calculates the sigma parameter as the square root of half the empirical second moment.

Usage

mlrayleigh(x, na.rm = FALSE, ...)

Arguments

x	a (non-empty) numeric vector of data values.
na.rm	logical. Should missing values be removed?
...	currently affects nothing.

Details

For the density function of the Rayleigh distribution see Rayleigh.

Value

mlrayleigh returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for sigma and the following attributes:

model	The name of the model.
density	The density associated with the estimates.
logLik	The loglikelihood at the maximum.
support	The support of the density.
n	The number of observations.
call	The call as captured my match.call

References

Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 18. Wiley, New York.

See Also

Rayleigh for the Rayleigh density.

Examples

mlrayleigh(precip)

Example output

Maximum likelihood estimates for the Rayleigh model 
sigma  
26.48  

univariateML documentation built on Jan. 25, 2022, 5:09 p.m.