mllogis: Logistic distribution maximum likelihood estimation

Description Usage Arguments Details Value References See Also Examples

View source: R/mllogis.R

Description

Calculates the estimates using nlm with an exponential transform of the location parameter.

Usage

1
mllogis(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 logistic distribution see Logistic.

Value

mllogis returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for location and scale 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 23. Wiley, New York.

See Also

Logistic for the Logistic density, nlm for the optimizer this function uses.

Examples

1

Example output

Maximum likelihood estimates for the Logistic model 
location     scale  
  35.638     7.737  

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