# pysal.explore.spaghetti.NetworkK¶

class pysal.explore.spaghetti.NetworkK(ntw, pointpattern, nsteps=10, permutations=99, threshold=0.5, distribution='poisson', lowerbound=None, upperbound=None)[source]

Compute a network constrained K statistic. This requires the capability to compute a distance matrix between two point patterns. In this case one will be observed and one will be simulated.

Notes

Based on [OY01].

Attributes: lam : float lambda value

Methods

 computeenvelope() compute upper and lower bounds of envelope computeobserved() compute the observed nearest computepermutations() compute permutations of the nearest setbounds(nearest) set upper and lower bounds validatedistribution() enusure statistical distribution is supported
__init__(ntw, pointpattern, nsteps=10, permutations=99, threshold=0.5, distribution='poisson', lowerbound=None, upperbound=None)

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

Methods

 __init__(ntw, pointpattern[, nsteps, …]) Initialize self. computeenvelope() compute upper and lower bounds of envelope computeobserved() compute the observed nearest computepermutations() compute permutations of the nearest setbounds(nearest) set upper and lower bounds validatedistribution() enusure statistical distribution is supported