spreg.dgp.dgp_gns

spreg.dgp.dgp_gns(u, xb, wxg, w, rho=0.5, lam=0.2, model='sar', imethod='power_exp', ybin=False)

dgp_gns: generates y for general nested model with sar or ma errors

with xb, wxg, weights, spatial parameter rho, spatial parameter lambda, model for spatial process, error term, method for inverse transform

Examples

>>> import numpy as np
>>> import libpysal
>>> from spreg import make_x, make_xb, make_wx, make_wxg, dgp_gns
>>> rng = np.random.default_rng(12345)
>>> u = make_x(rng,25,mu=[0],varu=[1], method='normal')
>>> x = make_x(rng,25,mu=[0],varu=[1])
>>> xb = make_xb(x,[1,2])
>>> w  = libpysal.weights.lat2W(5, 5)
>>> w.transform = "r"
>>> wx = make_wx(x,w)
>>> wxg = make_wxg(wx,[2])
>>> dgp_gns(u,xb,wxg,w)[0:5,:]
array([[18.04158549],
       [14.96336153],
       [11.95902806],
       [12.44108728],
       [15.47860632]])