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

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

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.


[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. <https://cran.r-project.org/web/packages/CircStats/CircStats.pdf>


>>> 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>)