def model_dfm(endog=None, params=None, factor_order=2):
if endog is None:
levels = macrodata[['realgdp', 'realcons']]
endog = np.log(levels).iloc[:21].diff().iloc[1:] * 400
if params is None:
params = np.r_[0.5, 1., 1.5, 2., 0.9, 0.1]
# Model
mod = DynamicFactor(endog, k_factors=1, factor_order=factor_order)
mod.update(params)
ssm = mod.ssm
ssm.filter_univariate = True
init = Initialization(ssm.k_states, 'diffuse')
ssm.initialize(init)
return mod, ssm
def model_dfm(endog=None, params=None, factor_order=2):
if endog is None:
endog = (np.log(
macrodata[['realgdp','realcons']]).iloc[:21].diff().iloc[1:] * 400)
if params is None:
params = np.r_[0.5, 1., 1.5, 2., 0.9, 0.1]
# Model
mod = DynamicFactor(endog, k_factors=1, factor_order=factor_order)
mod.update(params)
ssm = mod.ssm
ssm.filter_univariate = True
init = Initialization(ssm.k_states, 'diffuse')
ssm.initialize(init)
return mod, ssm