circular (version 0.3-4)

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, rho, tol = 1e-15, max.iter = 100)
## 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 missing the maximum likelihood estimate of the mean direction is calculated.

rho

if missing the maximum likelihood estimate of the concentration parameter is calculated.

tol

precision of the estimation.

max.iter

maximum number of iterations.

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().
• mu
  the estimate of the mean direction or the value supplied.
• 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.

See Also

mean.circular

Examples

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