pysal.explore.inequality.gini.Gini_Spatial¶

class pysal.explore.inequality.gini.Gini_Spatial(x, w, permutations=99)[source]¶

Spatial Gini coefficient

Provides for computationally based inference regarding the contribution of spatial neighbor pairs to overall inequality across a set of regions. See [RS13].

Parameters:	y : array (n,1) attribute w : binary spatial weights object permutations : int (default = 99) number of permutations for inference

Examples

>>> import pysal.lib
>>> import numpy as np
>>> from pysal.explore.inequality.gini import Gini_Spatial

Use data from the 32 Mexican States, Decade frequency 1940-2010

>>> f=pysal.lib.io.open(pysal.lib.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]))

Define regime neighbors

>>> regimes=np.array(f.by_col('hanson98'))
>>> w = pysal.lib.weights.block_weights(regimes)
>>> np.random.seed(12345)
>>> gs = Gini_Spatial(y[:,0],w)
>>> gs.p_sim
0.04
>>> gs.wcg
4353856.0
>>> gs.e_wcg
4170356.7474747472

Thus, the amount of inequality between pairs of states that are not in the same regime (neighbors) is significantly higher than what is expected under the null of random spatial inequality.

Attributes:

g : float Gini coefficient wg : float Neighbor inequality component (geographic inequality) wcg : float Non-neighbor inequality component (geographic complement inequality) wcg_share : float Share of inequality in non-neighbor component If Permuations > 0 p_sim : float pseudo p-value for spatial gini e_wcg : float expected value of non-neighbor inequality component (level) from permutations s_wcg : float standard deviation non-neighbor inequality component (level) from permutations z_wcg : float z-value non-neighbor inequality component (level) from permutations p_z_sim : float pseudo p-value based on standard normal approximation of permutation based values

__init__(x, w, permutations=99)[source]¶

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(x, w[, permutations])

Initialize self.