# vonmisesmle¶

astropy.stats.circstats.vonmisesmle(data, axis=None)[source]

Computes the Maximum Likelihood Estimator (MLE) for the parameters of the von Mises distribution.

Parameters: data : numpy.ndarray or Quantity Array of circular (directional) data, which is assumed to be in radians whenever data is numpy.ndarray. axis : int, optional Axis along which the mle will be computed. mu : float or Quantity the mean (aka location parameter). kappa : float or dimensionless Quantity the concentration parameter.

References

 [1] S. R. Jammalamadaka, A. SenGupta. “Topics in Circular Statistics”. Series on Multivariate Analysis, Vol. 5, 2001.
 [2] C. Agostinelli, U. Lund. “Circular Statistics from ‘Topics in Circular Statistics (2001)’”. 2015.

Examples

>>> import numpy as np
>>> from astropy.stats import vonmisesmle
>>> from astropy import units as u
>>> data = np.array([130, 90, 0, 145])*u.deg
>>> vonmisesmle(data) # doctest: +FLOAT_CMP
(<Quantity 101.16894320013179 deg>, <Quantity 1.49358958737054>)