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

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

datandarray or Quantity

Array of circular (directional) data, which is assumed to be in radians whenever data is numpy.ndarray.

axispython:int, optional

Axis along which the mle will be computed.

mupython:float or Quantity

The mean (aka location parameter).

kappapython:float or Quantity [:ref: ‘dimensionless’]

The concentration parameter.



S. R. Jammalamadaka, A. SenGupta. “Topics in Circular Statistics”. Series on Multivariate Analysis, Vol. 5, 2001.


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) 
(<Quantity 101.16894320013179 deg>, <Quantity 1.49358958737054>)