mlkumar: Kumaraswamy distribution maximum likelihood estimation

Description Usage Arguments Details Value References See Also Examples

View source: R/mlkumar.R

Description

Uses Newton-Raphson to estimate the parameters of the Kumaraswamy distribution.

Usage

1
mlkumar(x, na.rm = FALSE, ...)

Arguments

x

a (non-empty) numeric vector of data values.

na.rm

logical. Should missing values be removed?

...

a0 is an optional starting value for the a parameter. rel.tol is the relative accuracy requested, defaults to .Machine$double.eps^0.25. iterlim is a positive integer specifying the maximum number of iterations to be performed before the program is terminated (defaults to 100).

Details

For the density function of the Kumaraswamy distribution see Kumaraswamy.

Value

mlkumar returns an object of class univariateML. This is a named numeric vector with maximum likelihood estimates for a and b 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

Jones, M. C. "Kumaraswamy's distribution: A beta-type distribution with some tractability advantages." Statistical Methodology 6.1 (2009): 70-81.

Kumaraswamy, Ponnambalam. "A generalized probability density function for double-bounded random processes." Journal of Hydrology 46.1-2 (1980): 79-88.

See Also

Kumaraswamy for the Kumaraswamy density.

Examples

1
AIC(mlkumar(USArrests$Rape / 100))

Example output

[1] -96.06926

univariateML documentation built on Aug. 6, 2020, 1:11 a.m.