36 Spatio-temporal Models

Code

import numpy as np
import libpysal
import spreg

Code

db = libpysal.io.open(libpysal.examples.get_path("columbus.dbf"),'r')

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y = np.array(db.by_col("HOVAL"))
y = np.reshape(y, (49,1))

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X = []
X.append(db.by_col("INC"))
X.append(db.by_col("CRIME"))
X = np.array(X).T

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w = libpysal.weights.Rook.from_shapefile(libpysal.examples.get_path("columbus.shp"))

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w.transform = 'r'

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from spreg import GM_Lag
np.set_printoptions(suppress=True) #prevent scientific format
reg=GM_Lag(y, X, w=w, w_lags=2, name_x=['inc', 'crime'], name_y='hoval', name_ds='columbus')
reg.betas
np.array([[45.30170561],
       [ 0.62088862],
       [-0.48072345],
       [ 0.02836221]])

array([[45.30170561],
       [ 0.62088862],
       [-0.48072345],
       [ 0.02836221]])

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