Rayleigh distribution maximum likelihood estimation

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.

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

Details

For the density function of the Rayleigh distribution see Rayleigh.

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)
#> Maximum likelihood estimates for the Rayleigh model 
#> sigma  
#> 26.48