mle.vonmises: von Mises Maximum Likelihood Estimates
In circular: Circular Statistics

Description Usage Arguments Details Value Author(s) References See Also Examples

Computes the maximum likelihood estimates for the parameters of a von Mises distribution: the mean direction and the concentration parameter.

mle.vonmises(x, mu=NULL, kappa=NULL, bias=FALSE, control.circular=list())
## S3 method for class 'mle.vonmises'
print(x,
    digits = max(3, getOption("digits") - 3), ...)

`x`	a vector. The object is coerced to class `circular`.
`mu`	if `NULL` the maximum likelihood estimate of the mean direction is calculated. If provided it is coerced to a class `circular`.
`kappa`	if `NULL` the maximum likelihood estimate of the concentration parameter is calculated.
`bias`	logical, if `TRUE`, the estimate for kappa is computed with a bias corrected method. Default is `FALSE`, i.e. no bias correction.
`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.

Best and Fisher (1981) show that the MLE of kappa is seriously biased when both sample size and mean resultant length are small. They suggest a bias-corrected estimate for kappa when n < 16.

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`.
`kappa`	the estimate of the concentration parameter or the value supplied
`se.mu`	the standard error for the estimate of the mean direction (0 if the value is supplied) in the same units of `mu`.
`se.kappa`	the standard error for the estimate of the concentration parameter (0 if the value is supplied).
`est.mu`	TRUE if the estimator is reported.
`est.kappa`	TRUE if the estimator is reported.

Claudio Agostinelli and Ulric Lund

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

Best, D. and Fisher N. (1981). The bias of the maximum likelihood estimators of the von Mises-Fisher concentration parameters. Communications in Statistics - Simulation and Computation, B10(5), 493-502.

mean.circular and mle.vonmises.bootstrap.ci

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x <- rvonmises(n=50, mu=circular(0), kappa=5)
mle.vonmises(x) # estimation of mu and kappa
mle.vonmises(x, mu=circular(0)) # estimation of kappa only

Attaching package: 'circular'

The following objects are masked from 'package:stats':

    sd, var


Call:
mle.vonmises(x = x)

mu: -0.04609  ( 0.07739 )

kappa: 3.887  ( 0.6979 )


Call:
mle.vonmises(x = x, mu = circular(0))

mu: 0  ( 0 )

kappa: 3.864  ( 0.6932 )

mu is known