mllaplace: Laplace distribution maximum likelihood estimation

In univariateML: Maximum Likelihood Estimation for Univariate Densities

Description

The maximum likelihood estimate of mu is the sample median while the maximum likelihood estimate of sigma is mean absolute deviation from the median.

Usage

mllaplace(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 Laplace distribution see Laplace.

Value

mllaplace returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for mu and 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 2, Chapter 24. Wiley, New York.

See Also

Laplace for the Laplace density.

Examples

mllaplace(precip)

Example output

Maximum likelihood estimates for the Laplace model 
   mu  sigma  
36.60  10.49  

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