esda.Spatial_Pearson

class esda.Spatial_Pearson(connectivity=None, permutations=999)[source]

Global Spatial Pearson Statistic

__init__(connectivity=None, permutations=999)[source]

Initialize a spatial pearson estimator

Parameters:
connectivity: scipy.sparse matrix object

the connectivity structure describing the relationships between observed units. Will be row-standardized.

permutations: int

the number of permutations to conduct for inference. if < 1, no permutational inference will be conducted.

Attributes:
association_: numpy.ndarray (2,2)

array containg the estimated Lee spatial pearson correlation coefficients, where element [0,1] is the spatial correlation coefficient, and elements [0,0] and [1,1] are the “spatial smoothing factor”

reference_distribution_: numpy.ndarray (n_permutations, 2,2)

distribution of correlation matrices for randomly-shuffled maps.

significance_: numpy.ndarray (2,2)

permutation-based p-values for the fraction of times the observed correlation was more extreme than the simulated correlations.

Methods

__init__([connectivity, permutations])

Initialize a spatial pearson estimator

fit(x, y)

bivariate spatial pearson's R based on Eq.

get_params([deep])

Get parameters for this estimator.

set_params(**params)

Set the parameters of this estimator.