print g11res
llf = loglike_GARCH11(g11res, errgjr4-errgjr4.mean())
print llf[0]
if 'rpyfit' in examples:
from rpy import r
r.library('fGarch')
f = r.formula('~garch(1, 1)')
fit = r.garchFit(f, data = errgjr4-errgjr4.mean(), include_mean=False)
if 'rpysim' in examples:
from rpy import r
f = r.formula('~garch(1, 1)')
#fit = r.garchFit(f, data = errgjr4)
x = r.garchSim( n = 500)
print 'R acf', tsa.acf(np.power(x,2))[:15]
arma3 = Arma(np.power(x,2))
arma3res = arma3.fit(start_params=[-0.2,0.1,0.5],maxiter=5000)
print arma3res.params
arma3b = Arma(np.power(x,2))
arma3bres = arma3b.fit(start_params=[-0.2,0.1,0.5],maxiter=5000, method='bfgs')
print arma3bres.params
xr = r.garchSim( n = 100)
x = np.asarray(xr)
ggmod = Garch(x-x.mean())
ggmod.nar = 1
ggmod.nma = 1
ggmod._start_params = np.array([-0.6, 0.1, 0.2, 0.0])
ggres = ggmod.fit(start_params=np.array([-0.6, 0.1, 0.2, 0.0]), maxiter=1000)
print(g11res)
llf = loglike_GARCH11(g11res, errgjr4 - errgjr4.mean())
print(llf[0])
if 'rpyfit' in examples:
from rpy import r
r.library('fGarch')
f = r.formula('~garch(1, 1)')
fit = r.garchFit(f, data=errgjr4 - errgjr4.mean(), include_mean=False)
if 'rpysim' in examples:
from rpy import r
f = r.formula('~garch(1, 1)')
#fit = r.garchFit(f, data = errgjr4)
x = r.garchSim(n=500)
print('R acf', tsa.acf(np.power(x, 2))[:15])
arma3 = Arma(np.power(x, 2))
arma3res = arma3.fit(start_params=[-0.2, 0.1, 0.5], maxiter=5000)
print(arma3res.params)
arma3b = Arma(np.power(x, 2))
arma3bres = arma3b.fit(start_params=[-0.2, 0.1, 0.5],
maxiter=5000,
method='bfgs')
print(arma3bres.params)
xr = r.garchSim(n=100)
x = np.asarray(xr)
ggmod = Garch(x - x.mean())
ggmod.nar = 1
ggmod.nma = 1