Skew Normal distribution maximum likelihood estimation

Joint maximum likelihood estimation as implemented by fGarch::snormFit.

Usage

mlsnorm(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

mlsnorm returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for the parameters mean, sd, xi 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 Student t distribution see dsnorm.

References

Fernandez C., Steel M.F.J. (2000); On Bayesian Modelling of Fat Tails and Skewness, Preprint.

Examples

mlsnorm(precip)
#> Maximum likelihood estimates for the Skew Normal model 
#>    mean       sd       xi  
#> 34.6957  13.5471   0.8088