mlstd {univariateML}

Student-t distribution maximum likelihood estimation

Description

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.

Details

For the density function of the Student t-distribution see std.

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

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)