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 mle.vonmises
print(x,
digits = max(3, getOption("digits") - 3), ...)
Returns a list with the following components:
the match.call
result.
the estimate of the mean direction or the value supplied as an object of class circular
.
the estimate of the concentration parameter or the value supplied
the standard error for the estimate of the mean
direction (0 if the value is supplied) in the same units of mu
.
the standard error for the estimate of the concentration parameter (0 if the value is supplied).
TRUE if the estimator is reported.
TRUE if the estimator is reported.
a vector. The object is coerced to class
circular
.
if NULL
the maximum likelihood estimate of the mean
direction is calculated. If provided it is coerced to a class circular
.
if NULL
the maximum likelihood estimate of the
concentration parameter is calculated.
logical, if TRUE
, the estimate for kappa is
computed with a bias corrected method. Default is FALSE
,
i.e. no bias correction.
the attribute of the resulting objects (mu
)
integer indicating the precision to be used.
further arguments passed to or from other methods.
Claudio Agostinelli and Ulric Lund
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.
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
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
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