Python StatTestMC Examples

Example #1

File: try_mctools.py Project: AnaMP/statsmodels

import numpy as np
from scipy import stats
from statsmodels.sandbox.tools.mctools import StatTestMC
from statsmodels.sandbox.stats.diagnostic import (
                    acorr_ljungbox, unitroot_adf)

def normalnoisesim(nobs=500, loc=0.0):
    return (loc+np.random.randn(nobs))


def lb(x):
    s,p = acorr_ljungbox(x, lags=4)
    return np.r_[s, p]


mc1 = StatTestMC(normalnoisesim, lb)
mc1.run(5000, statindices=range(4))

print mc1.summary_quantiles([1,2,3], stats.chi2([2,3,4]).ppf,
                            varnames=['lag 1', 'lag 2', 'lag 3'],
                            title='acorr_ljungbox')
print '\n\n'

frac = [0.01, 0.025, 0.05, 0.1, 0.975]
crit = stats.chi2([2,3,4]).ppf(np.atleast_2d(frac).T)
print mc1.summary_cdf([1,2,3], frac, crit,
                      varnames=['lag 1', 'lag 2', 'lag 3'],
                      title='acorr_ljungbox')
print mc1.cdf(crit, [1,2,3])[1]

#----------------------

Example #2

File: try_mctools.py Project: kasunsp/pinalpha_mvp

import numpy as np
from scipy import stats
from statsmodels.sandbox.tools.mctools import StatTestMC
from statsmodels.sandbox.stats.diagnostic import (
                    acorr_ljungbox, unitroot_adf)

def normalnoisesim(nobs=500, loc=0.0):
    return (loc+np.random.randn(nobs))


def lb(x):
    s,p = acorr_ljungbox(x, lags=4)
    return np.r_[s, p]


mc1 = StatTestMC(normalnoisesim, lb)
mc1.run(5000, statindices=lrange(4))

print(mc1.summary_quantiles([1,2,3], stats.chi2([2,3,4]).ppf,
                            varnames=['lag 1', 'lag 2', 'lag 3'],
                            title='acorr_ljungbox'))
print('\n\n')

frac = [0.01, 0.025, 0.05, 0.1, 0.975]
crit = stats.chi2([2,3,4]).ppf(np.atleast_2d(frac).T)
print(mc1.summary_cdf([1,2,3], frac, crit,
                      varnames=['lag 1', 'lag 2', 'lag 3'],
                      title='acorr_ljungbox'))
print(mc1.cdf(crit, [1,2,3])[1])

#----------------------

Example #3

File: try_mctools.py Project: alfonsodiecko/PYTHON_DIST

import numpy as np
from scipy import stats
from statsmodels.sandbox.tools.mctools import StatTestMC
from statsmodels.sandbox.stats.diagnostic import acorr_ljungbox, unitroot_adf


def normalnoisesim(nobs=500, loc=0.0):
    return loc + np.random.randn(nobs)


def lb(x):
    s, p = acorr_ljungbox(x, lags=4)
    return np.r_[s, p]


mc1 = StatTestMC(normalnoisesim, lb)
mc1.run(5000, statindices=list(range(4)))

print(
    mc1.summary_quantiles(
        [1, 2, 3], stats.chi2([2, 3, 4]).ppf, varnames=["lag 1", "lag 2", "lag 3"], title="acorr_ljungbox"
    )
)
print("\n\n")

frac = [0.01, 0.025, 0.05, 0.1, 0.975]
crit = stats.chi2([2, 3, 4]).ppf(np.atleast_2d(frac).T)
print(mc1.summary_cdf([1, 2, 3], frac, crit, varnames=["lag 1", "lag 2", "lag 3"], title="acorr_ljungbox"))
print(mc1.cdf(crit, [1, 2, 3])[1])

# ----------------------