mle.wrappedcauchy: 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 mle.wrappedcauchy
print(x, digits = max(3, getOption("digits") - 3), …)

Arguments

a vector. The object is coerced to class circular.

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.

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.

References

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

Examples

Run this code

# NOT RUN {
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
# }