mle.wrappedcauchy: Wrapped Cauchy Maximum Likelihood Estimates

In circular: Circular Statistics

Wrapped Cauchy Maximum Likelihood Estimates

Description

Computes the maximum likelihood estimates for the parameters of a Wrapped Cauchy distribution: mean and concentration parameter.

Usage

mle.wrappedcauchy(x, mu = NULL, rho = NULL, tol = 1e-15, 
        max.iter = 100, control.circular = list())
## S3 method for class 'mle.wrappedcauchy'
print(x, digits = max(3, getOption("digits") - 3), ...)

Arguments

x	a vector. The object is coerced to class circular.
mu	if NULL the maximum likelihood estimate of the mean direction is calculated otherwise it is coerced to an object of class circular.
rho	if NULL the maximum likelihood estimate of the concentration parameter is calculated.
tol	precision of the estimation.
max.iter	maximum number of iterations.
control.circular	the attribute of the resulting objects (mu)
digits	integer indicating the precision to be used.
...	further arguments passed to or from other methods.

Value

Returns a list with the following components:

call	the match.call result.
mu	the estimate of the mean direction or the value supplied as an object of class circular.
rho	the estimate of the concentration parameter or the value supplied
convergence	TRUE if convergence is achieved.

Author(s)

Claudio Agostinelli and Ulric Lund

References

Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, Section 4.2.1, World Scientific Press, Singapore.

See Also

mean.circular

Examples

x <- rwrappedcauchy(n=50, mu=circular(0), rho=0.5)
mle.wrappedcauchy(x) # estimation of mu and rho
mle.wrappedcauchy(x, mu=circular(0)) # estimation of rho only

circular documentation built on Sept. 11, 2024, 8:21 p.m.