Student-t distribution maximum likelihood estimation

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

Usage

mlstd(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

mlstd returns an object of class

univariateML. This is a named numeric vector with maximum likelihood estimates for the parameters mean, sd, nu 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 std.

References

Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 13. Wiley, New York.

See also

std for the Student-t density.

Examples

mlstd(precip)
#> Maximum likelihood estimates for the Student-t model 
#>      mean         sd         nu  
#> 3.489e+01  1.361e+01  4.243e+07