giddy.rank.
Tau_Local
(x, y)[source]¶Local version of the classic Tau.
Decomposition of the classic Tau into local components.
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Notes
The equation for calculating local concordance statistic can be found in [Rey16] Equation (9).
Examples
>>> import libpysal as ps
>>> import numpy as np
>>> from giddy.rank import Tau_Local,Tau
>>> np.random.seed(10)
>>> f = ps.io.open(ps.examples.get_path("mexico.csv"))
>>> vnames = ["pcgdp%d"%dec for dec in range(1940, 2010, 10)]
>>> y = np.transpose(np.array([f.by_col[v] for v in vnames]))
>>> r = y / y.mean(axis=0)
>>> tau_local = Tau_Local(r[:,0],r[:,1])
>>> tau_local.tau_local
array([-0.03225806, 0.93548387, 0.80645161, 0.74193548, 0.93548387,
0.74193548, 0.67741935, 0.41935484, 1. , 0.5483871 ,
0.74193548, 0.93548387, 0.67741935, 0.74193548, 0.80645161,
0.74193548, 0.5483871 , 0.67741935, 0.74193548, 0.74193548,
0.5483871 , -0.16129032, 0.93548387, 0.61290323, 0.67741935,
0.48387097, 0.93548387, 0.61290323, 0.74193548, 0.41935484,
0.61290323, 0.61290323])
>>> tau_local.tau
0.6612903225806451
>>> tau_classic = Tau(r[:,0],r[:,1])
>>> tau_classic.tau
0.6612903225806451
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