return (drift+np.random.randn(nobs)).cumsum()
def adf20(x):
return unitroot_adf(x, 2, trendorder=0, autolag=None)
print(adf20(np.random.randn(100)))
mc2 = StatTestMC(randwalksim, adf20)
mc2.run(10000, statindices=[0,1])
frac = [0.01, 0.05, 0.1]
#bug
crit = np.array([-3.4996365338407074, -2.8918307730370025, -2.5829283377617176])[:,None]
print(mc2.summary_cdf([0], frac, crit,
varnames=['adf'],
title='adf'))
#bug
#crit2 = np.column_stack((crit, frac))
#print mc2.summary_cdf([0, 1], frac, crit,
# varnames=['adf'],
# title='adf')
print(mc2.quantiles([0]))
print(mc2.cdf(crit, [0]))
doplot=1
if doplot:
import matplotlib.pyplot as plt
mc1.plot_hist([3],stats.chi2([4]).pdf)
plt.title('acorr_ljungbox - MC versus chi2')
plt.show()
def adf20(x):
return unitroot_adf(x, 2, trendorder=0, autolag=None)
print adf20(np.random.randn(100))
mc2 = StatTestMC(randwalksim, adf20)
mc2.run(10000, statindices=[0, 1])
frac = [0.01, 0.05, 0.1]
#bug
crit = np.array(
[-3.4996365338407074, -2.8918307730370025, -2.5829283377617176])[:, None]
print mc2.summary_cdf([0], frac, crit, varnames=['adf'], title='adf')
#bug
#crit2 = np.column_stack((crit, frac))
#print mc2.summary_cdf([0, 1], frac, crit,
# varnames=['adf'],
# title='adf')
print mc2.quantiles([0])
print mc2.cdf(crit, [0])
doplot = 1
if doplot:
import matplotlib.pyplot as plt
mc1.plot_hist([3], stats.chi2([4]).pdf)
plt.title('acorr_ljungbox - MC versus chi2')
plt.show()
return (drift+np.random.randn(nobs)).cumsum()
def adf20(x):
return unitroot_adf(x, 2, trendorder=0, autolag=None)
print adf20(np.random.randn(100))
mc2 = StatTestMC(randwalksim, adf20)
mc2.run(10000, statindices=[0,1])
frac = [0.01, 0.05, 0.1]
#bug
crit = np.array([-3.4996365338407074, -2.8918307730370025, -2.5829283377617176])[:,None]
print mc2.summary_cdf([0], frac, crit,
varnames=['adf'],
title='adf')
#bug
#crit2 = np.column_stack((crit, frac))
#print mc2.summary_cdf([0, 1], frac, crit,
# varnames=['adf'],
# title='adf')
print mc2.quantiles([0])
print mc2.cdf(crit, [0])
doplot=1
if doplot:
import matplotlib.pyplot as plt
mc1.plot_hist([3],stats.chi2([4]).pdf)
plt.title('acorr_ljungbox - MC versus chi2')
plt.show()
def adf20(x):
return unitroot_adf(x, 2, trendorder=0, autolag=None)
print(adf20(np.random.randn(100)))
mc2 = StatTestMC(randwalksim, adf20)
mc2.run(10000, statindices=[0, 1])
frac = [0.01, 0.05, 0.1]
# bug
crit = np.array([-3.4996365338407074, -2.8918307730370025, -2.5829283377617176])[:, None]
print(mc2.summary_cdf([0], frac, crit, varnames=["adf"], title="adf"))
# bug
# crit2 = np.column_stack((crit, frac))
# print mc2.summary_cdf([0, 1], frac, crit,
# varnames=['adf'],
# title='adf')
print(mc2.quantiles([0]))
print(mc2.cdf(crit, [0]))
doplot = 1
if doplot:
import matplotlib.pyplot as plt
mc1.plot_hist([3], stats.chi2([4]).pdf)
plt.title("acorr_ljungbox - MC versus chi2")
plt.show()
