esda.Moran_Rate

class esda.Moran_Rate(e, b, w, adjusted=True, transformation='r', permutations=999, two_tailed=True)[source]

Adjusted Moran’s I Global Autocorrelation Statistic for Rate Variables [AR99]

Parameters:
units

wW | Graph

spatial weights instance as W or Graph aligned with e and b

variable

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

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

two-tailed, otherwise they are one tailed.

p_values

Examples

>>> import libpysal
>>> w = libpysal.io.open(libpysal.examples.get_path("sids2.gal")).read()
>>> f = libpysal.io.open(libpysal.examples.get_path("sids2.dbf"))
>>> e = np.array(f.by_col('SID79'))
>>> b = np.array(f.by_col('BIR79'))
>>> from esda.moran import Moran_Rate
>>> mi = Moran_Rate(e, b,  w, two_tailed=False)
>>> "%6.4f" % mi.I
'0.1662'
>>> "%6.4f" % mi.p_norm
'0.0042'
Attributes:
if adjusted is True, y is standardized rates otherwise, y is raw rates

wW | Graph

original w object

otherwise they are one-tailed.

vector of I values for permuted samples

p-value based on permutations (one-sided) null: spatial randomness alternative: the observed I is extreme if it is either extremely greater or extremely lower than the values obtained from permutaitons

average value of I from permutations

variance of I from permutations

standard deviation of I under permutations.

standardized I based on permutations

p-value based on standard normal approximation from

__init__(e, b, w, adjusted=True, transformation='r', permutations=999, two_tailed=True)[source]

Methods

__init__(e, b, w[, adjusted, ...])

by_col(df, events, populations[, w, ...])

Function to compute a Moran_Rate statistic on a dataframe

classmethod by_col(df, events, populations, w=None, inplace=False, pvalue='sim', outvals=None, swapname='', **stat_kws)[source]

Function to compute a Moran_Rate statistic on a dataframe

Parameters:
events are stored. If one population column is provided, it is used for all event columns. If more than one population column is provided but there is not a population for every event column, an exception will be raised.

wW | Graph

spatial weights instance as W or Graph aligned with the dataframe. If not provided, this is searched for in the dataframe’s metadata

return a series contaning the results of the computation. If operating inplace, the derived columns will be named ‘column_moran_rate’

the Moran_Rate statistic’s documentation for available p-values

Moran_Rate statistic

documentation for the Moran_Rate statistic.

Returns:
the relevant columns attached.