esda.join_counts — Spatial autocorrelation statistics for binary attributes

New in version 1.0.

Spatial autocorrelation for binary attributes

class pysal.esda.join_counts.Join_Counts(y, w)

Binary Join Counts

Parameters:

y : array

binary variable measured across n spatial units

w : W

spatial weights instance

Examples

Replicate example from anselin and rey

>>> import numpy as np
>>> w=pysal.lat2W(4,4)
>>> y=np.ones(16)
>>> y[0:8]=0
>>> jc=Join_Counts(y,w)
>>> jc.bb
10.0
>>> jc.zbb
1.2060453783110545
>>> jc.bw
4.0
>>> jc.zbw
-3.2659863237109046
>>> jc.Ebw
12.0
>>> jc.bw
4.0
>>> jc.Vbw
6.0
>>> np.sqrt(jc.Vbw)
2.4494897427831779
>>> 

Attributes

y	array	original variable
w	W	original w object
bb	float	number of black-black joins
ww	float	number of white-white joins
bw	float	number of black-white joins
J	float	number of joins
Ebb	float	expected value of bb under free sampling
Eww	float	expected value of ww under free sampling
Ebw	float	expected value of bw under free sampling
Vbb	float	variance of bb under free sampling
Vww	float	variance of ww under free sampling
Vbw	float	variance of bw under free sampling
zbb	float	z-value for bb under free sampling
zww	float	z-value for ww under free sampling
zbw	float	z-value for bw under free sampling