CCd (version 1.1)

cc.mle: Maximum likelihood estimation of the CC distribution

Description

Maximum likelihood estimation of the CC distribution.

Usage

cc.mle(y)
cc.mle0(y, tol = 1e-7)

Value

A list including:

param

For the cc.mle() a vector of the \(\lambda\) and \(\mu\) parameters.

lambda

For the cc.mle0() the \(\lambda\) parameter.

loglik

The value of the maximized log-likelihood.

Arguments

y

A vector with integer values.

tol

The tolerance value to terminate the maximization algorithm.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris .

Details

The function cc.mle0() uses the optimize function to perform MLE when the location parameter is zero, just as proposed by Papadatos (2022). The function cc.mle() uses the optim function when the location is not assumed zero.

References

Papadatos N. (2022). The characteristic function of the discrete Cauchy distribution In Memory of T. Cacoullos. Journal of Statistical Theory and Practice, 16(3): 47.

See Also

loc0.test, dcc, cc.reg

Examples

y <- round( rcauchy(100, 3, 10) )
cc.mle(y)

y <- round( rcauchy(100, 0, 10) )
cc.mle0(y)