esda.Geary

class esda.Geary(y, w, transformation='r', permutations=999)

Global Geary C Autocorrelation statistic

Parameters

yarray

(n, 1) attribute vector

wW

spatial weights

transformation{‘R’, ‘B’, ‘D’, ‘U’, ‘V’}

weights transformation, default is row-standardized. Other options include “B”: binary, “D”: doubly-standardized, “U”: untransformed (general weights), “V”: variance-stabilizing.

permutationsint

number of random permutations for calculation of pseudo-p_values

Notes

Technical details and derivations can be found in [CO81].

Examples

>>> import libpysal
>>> from esda.geary import Geary
>>> w = libpysal.io.open(libpysal.examples.get_path("book.gal")).read()
>>> f = libpysal.io.open(libpysal.examples.get_path("book.txt"))
>>> y = np.array(f.by_col['y'])
>>> c = Geary(y,w,permutations=0)
>>> round(c.C,7)
0.3330108
>>> round(c.p_norm,7)
9.2e-05
>>>

Attributes

yarray

original variable

wW

spatial weights

permutationsint

number of permutations

Cfloat

value of statistic

ECfloat

expected value

VCfloat

variance of G under normality assumption

z_normfloat

z-statistic for C under normality assumption

z_randfloat

z-statistic for C under randomization assumption

p_normfloat

p-value under normality assumption (one-tailed)

p_randfloat

p-value under randomization assumption (one-tailed)

simarray

(if permutations!=0) vector of I values for permutated samples

p_simfloat

(if permutations!=0) p-value based on permutations (one-tailed) null: sptial randomness alternative: the observed C is extreme it is either extremely high or extremely low

EC_simfloat

(if permutations!=0) average value of C from permutations

VC_simfloat

(if permutations!=0) variance of C from permutations

seC_simfloat

(if permutations!=0) standard deviation of C under permutations.

z_simfloat

(if permutations!=0) standardized C based on permutations

p_z_simfloat

(if permutations!=0) p-value based on standard normal approximation from permutations (one-tailed)

Methods

by_col(df, cols[, w, inplace, pvalue, outvals])

Function to compute a Geary statistic on a dataframe

__init__(self, y, w, transformation='r', permutations=999)

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

Methods

__init__(self, y, w[, transformation, …])	Initialize self.
by_col(df, cols[, w, inplace, pvalue, outvals])	Function to compute a Geary statistic on a dataframe