def test_breaks_hansen(self):
# > sc = sctest(ginv ~ ggdp + lint, type="Nyblom-Hansen")
# > mkhtest(sc, 'breaks_nyblom_hansen', 'BB')
breaks_nyblom_hansen = dict(statistic=1.0300792740544484, pvalue=0.1136087530212015, parameters=(), distr="BB")
bh = smsdia.breaks_hansen(self.res)
assert_almost_equal(bh[0], breaks_nyblom_hansen["statistic"], decimal=13)
def test_breaks_hansen(self):
#> sc = sctest(ginv ~ ggdp + lint, type="Nyblom-Hansen")
#> mkhtest(sc, 'breaks_nyblom_hansen', 'BB')
breaks_nyblom_hansen = dict(statistic=1.0300792740544484,
pvalue=0.1136087530212015,
parameters=(), distr='BB')
bh = smsdia.breaks_hansen(self.res)
assert_almost_equal(bh[0], breaks_nyblom_hansen['statistic'],
decimal=13)
plt.plot(rcusum)
plt.plot(rcusumci[0])
plt.plot(rcusumci[1])
plt.figure()
plt.plot(rresid)
plt.plot(np.abs(rresid))
print('cusum test reject:')
print(((rcusum[1:] > rcusumci[1]) | (rcusum[1:] < rcusumci[0])).any())
rresid2, rparams2, rypred2, rresid_standardized2, rresid_scaled2, rcusum2, rcusumci2 = \
recursive_olsresiduals(res1, skip)
#assert_almost_equal(rparams[skip+1:], rparams2[skip:-1],13)
assert_almost_equal(rparams[skip:], rparams2[skip:], 13)
#np.c_[rparams[skip+1:], rparams2[skip:-1]]
#plt.show()
#################### Example break test
H, crit95 = breaks_hansen(res1)
print(H)
print(crit95)
supb, pval, crit = breaks_cusumolsresid(res1.resid)
print(supb, pval, crit)
##check whether this works directly: Ploberger/Kramer framing of standard cusum
##no, it's different, there is another denominator
#print breaks_cusumolsresid(rresid[skip:])
#this function is still completely wrong, cut and paste does not apply
#print breaks_cusum(rresid[skip:])
