def __init__(self):
     self.mteObj = mo.hackit()
     self.weightObj = wo.weightGenerator()
    Mainly test for the heckit case and the the linear but non-normal case
'''

import sampleSimulation as ss
import numpy as np


Y,D,X,Z = ss.underiv_data(5000)

import mteObj as mo
x0 = np.mean(X, 0)
x0.shape = (1,2)


# calculate the MTE
testObj = mo.hackit()
testObj.assignData(Y, D, X, Z)

''' 
    test heck it
'''
linear = 1
normal = 1
LLRMTE = 0
polyOrder = 4
testObj.assignParam(linear, normal, LLRMTE, polyOrder)
testObj.estimateParam()

assert abs(testObj.betaTreat[0] - 0.24)<0.01
assert abs(testObj.betaTreat[1] - 0.8)<0.01
assert abs(testObj.betaTreat[2] - 0.4)<0.01
예제 #3
0
 '''
'''
    Mainly test for the heckit case and the the linear but non-normal case
'''

import sampleSimulation as ss
import numpy as np

Y, D, X, Z = ss.underiv_data(5000)

import mteObj as mo
x0 = np.mean(X, 0)
x0.shape = (1, 2)

# calculate the MTE
testObj = mo.hackit()
testObj.assignData(Y, D, X, Z)
''' 
    test heck it
'''
linear = 1
normal = 1
LLRMTE = 0
polyOrder = 4
testObj.assignParam(linear, normal, LLRMTE, polyOrder)
testObj.estimateParam()

assert abs(testObj.betaTreat[0] - 0.24) < 0.01
assert abs(testObj.betaTreat[1] - 0.8) < 0.01
assert abs(testObj.betaTreat[2] - 0.4) < 0.01
assert abs(testObj.betaTreat[3] + 0.012) < 0.001