Exponential distribution maximum likelihood estimation

The maximum likelihood estimate of rate is the inverse sample mean.

Usage

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

Arguments

x: a (non-empty) numeric vector of data values.
na.rm: logical. Should missing values be removed? If FALSE, the function fails when x contains missing values.
...: currently affects nothing.

Value

mlexp returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for rate 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 by match.call
continuous: Is the density continuous or discrete?

Details

For the density function of the exponential distribution see Exponential.

References

Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 19. Wiley, New York.

Examples

mlexp(precip)
#> Maximum likelihood estimates for the Exponential model 
#>    rate  
#> 0.02867