vtest(data, mu=0.0, axis=None, weights=None)¶
Performs the Rayleigh test of uniformity where the alternative hypothesis H1 is assumed to have a known mean angle
Array of circular (directional) data, which is assumed to be in radians whenever
Quantity[:ref: ‘angle’], optional
Mean angle. Assumed to be known.
Axis along which the V test will be performed.
In case of grouped data, the i-th element of
weightsrepresents a weighting factor for each group such that
sum(weights, axis)equals the number of observations. See , remark 1.4, page 22, for detailed explanation.
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>
M. Chirstman., C. Miller. “Testing a Sample of Directions for Uniformity.” Lecture Notes, STA 6934/5805. University of Florida, 2007.
>>> import numpy as np >>> from astropy.stats import vtest >>> from astropy import units as u >>> data = np.array([130, 90, 0, 145])*u.deg >>> vtest(data) <Quantity 0.6223678199713766>