##################################################
# Define exit message to send to email upon fail #
##################################################
#atexit.register(fail_mail, start_date, passwd)
#generate decent guesses
lam_0_e, lam_1_e, delta_0_e, delta_1_e, mu_e, phi_e, sigma_e \
= bsr_constructor(k_ar=k_ar, neqs=neqs)
delta_0_e, delta_1_e, mu_e, phi_e, sigma_e = pass_ols(
var_data=mod_data,
freq="M",
lat=0,
k_ar=k_ar,
neqs=neqs,
delta_0=delta_0_e,
delta_1=delta_1_e,
mu=mu_e,
phi=phi_e,
sigma=sigma_e)
delta_1_e[np.argmax(mod_data.columns == 'fed_funds')] = 1
print "Initial estimation"
bsr_model = Affine(yc_data=mod_yc_data,
var_data=mod_data,
lam_0_e=lam_0_e,
lam_1_e=lam_1_e,
delta_0_e=delta_0_e,
delta_1_e=delta_1_e,
mu_e=mu_e,
mu_e[-latent:, 0] = ma.masked
phi_e[-latent:, -latent:] = ma.masked
sigma_e[:, :] = ma.masked
sigma_e[:, :] = ma.nomask
sigma_e[-latent:, -latent:] = np.identity(latent)
# sigma_e[-latent:, -latent:] = ma.masked
delta_0_e, delta_1_e, mu_e, phi_e, sigma_e = pass_ols(
var_data=macro_data_use,
freq="Q",
lat=latent,
k_ar=k_ar,
neqs=neqs,
delta_0=delta_0_e,
delta_1=delta_1_e,
mu=mu_e,
phi=phi_e,
sigma=sigma_e,
rf_rate=rf_rate,
)
mod_init = Affine(
yc_data=yc_data_use,
var_data=macro_data_use,
latent=latent,
lam_0_e=lam_0_e,
lam_1_e=lam_1_e,
delta_0_e=delta_0_e,
mod_data = mod_data.ix[var_dates]
mod_yc_data = mod_yc_data.ix[yc_dates]
##################################################
# Define exit message to send to email upon fail #
##################################################
#atexit.register(fail_mail, start_date, passwd)
#generate decent guesses
lam_0_e, lam_1_e, delta_0_e, delta_1_e, mu_e, phi_e, sigma_e \
= bsr_constructor(k_ar=k_ar, neqs=neqs)
delta_0_e, delta_1_e, mu_e, phi_e, sigma_e = pass_ols(var_data=mod_data,
freq="M", lat=0,
k_ar=k_ar, neqs=neqs,
delta_0=delta_0_e,
delta_1=delta_1_e,
mu=mu_e, phi=phi_e,
sigma=sigma_e)
delta_1_e[np.argmax(mod_data.columns == 'fed_funds')] = 1
print "Initial estimation"
bsr_model = Affine(yc_data=mod_yc_data, var_data=mod_data, lam_0_e=lam_0_e,
lam_1_e=lam_1_e, delta_0_e=delta_0_e, delta_1_e=delta_1_e,
mu_e=mu_e, phi_e=phi_e, sigma_e=sigma_e, mths=mths)
guess_length = bsr_model.guess_length
guess_params = [0.0000] * guess_length
print source
#align number of obs between yields and grab rf rate
#mth_only = to_mth(mod_yc_data)
neqs = len(macro_data_use.columns)
#This is a constructor function for easiloy setting up the system ala Ang and
#Piazzessi 2003
lam_0_e, lam_1_e, delta_0_e, delta_1_e, mu_e, phi_e, sigma_e \
= ap_constructor(k_ar=k_ar, neqs=neqs, lat=latent)
delta_0_e, delta_1_e, mu_e, phi_e, sigma_e = pass_ols(var_data=macro_data_use,
freq="Q",
lat=latent,
k_ar=k_ar,
neqs=neqs,
delta_0=delta_0_e,
delta_1=delta_1_e,
mu=mu_e,
phi=phi_e,
sigma=sigma_e,
rf_rate=rf_rate)
mod_init = Affine(yc_data=yc_data_use,
var_data=macro_data_use,
latent=latent,
no_err=[0, 2, 4],
lam_0_e=lam_0_e,
lam_1_e=lam_1_e,
delta_0_e=delta_0_e,
delta_1_e=delta_1_e,
mu_e=mu_e,
