mle.vonmises {circular} | R Documentation |
von Mises Maximum Likelihood Estimates
Description
Computes the maximum likelihood estimates for the parameters of a von Mises distribution: the mean direction and the concentration parameter.
Usage
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), ...)
Arguments
x |
a vector. The object is coerced to class
|
mu |
if |
kappa |
if |
bias |
logical, if |
control.circular |
the attribute of the resulting objects ( |
digits |
integer indicating the precision to be used. |
... |
further arguments passed to or from other methods. |
Details
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.
Value
Returns a list with the following components:
call |
the |
mu |
the estimate of the mean direction or the value supplied as an object of class |
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 |
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. |
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.
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.
See Also
mean.circular
and mle.vonmises.bootstrap.ci
Examples
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