def __init__(self, y, x, regimes, w=None, constant_regi='many',\
cols2regi='all', method='full', epsilon=0.0000001,\
regime_lag_sep=False, cores=None, spat_diag=False,\
vm=False, name_y=None, name_x=None,\
name_w=None, name_ds=None, name_regimes=None):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
USER.check_spat_diag(spat_diag, w)
name_y = USER.set_name_y(name_y)
self.name_y = name_y
self.name_x_r = USER.set_name_x(name_x, x) + [USER.set_name_yend_sp(name_y)]
self.method = method
self.epsilon = epsilon
self.name_regimes = USER.set_name_ds(name_regimes)
self.constant_regi=constant_regi
self.n = n
cols2regi = REGI.check_cols2regi(constant_regi, cols2regi, x, add_cons=False)
self.cols2regi = cols2regi
self.regimes_set = REGI._get_regimes_set(regimes)
self.regimes = regimes
self.regime_lag_sep = regime_lag_sep
self._cache = {}
self.name_ds = USER.set_name_ds(name_ds)
self.name_w = USER.set_name_w(name_w, w)
USER.check_regimes(self.regimes_set,self.n,x.shape[1])
if regime_lag_sep == True:
if not (set(cols2regi) == set([True]) and constant_regi == 'many'):
raise Exception, "All variables must vary by regimes if regime_lag_sep = True."
cols2regi += [True]
w_i,regi_ids,warn = REGI.w_regimes(w, regimes, self.regimes_set, transform=True, get_ids=True, min_n=len(cols2regi)+1)
set_warn(self,warn)
else:
cols2regi += [False]
if set(cols2regi) == set([True]) and constant_regi == 'many':
self.y = y
self.ML_Lag_Regimes_Multi(y, x, w_i, w, regi_ids,\
cores=cores, cols2regi=cols2regi, method=method, epsilon=epsilon,\
spat_diag=spat_diag, vm=vm, name_y=name_y, name_x=name_x,\
name_regimes=self.name_regimes,\
name_w=name_w, name_ds=name_ds)
else:
#if regime_lag_sep == True:
# w = REGI.w_regimes_union(w, w_i, self.regimes_set)
name_x = USER.set_name_x(name_x, x,constant=True)
x, self.name_x = REGI.Regimes_Frame.__init__(self, x, \
regimes, constant_regi, cols2regi=cols2regi[:-1], names=name_x)
self.name_x.append("_Global_"+USER.set_name_yend_sp(name_y))
BaseML_Lag.__init__(self, y=y, x=x, w=w, method=method, epsilon=epsilon)
self.kf += 1 #Adding a fixed k to account for spatial lag.
self.chow = REGI.Chow(self)
self.aic = DIAG.akaike(reg=self)
self.schwarz = DIAG.schwarz(reg=self)
self.regime_lag_sep=regime_lag_sep
self.title = "MAXIMUM LIKELIHOOD SPATIAL LAG - REGIMES" + " (METHOD = " + method + ")"
SUMMARY.ML_Lag(reg=self, w=w, vm=vm, spat_diag=spat_diag, regimes=True)
def __init__(self, y, x, w, method='full', epsilon=0.0000001,
spat_diag=False, vm=False, name_y=None, name_x=None,
name_w=None, name_ds=None):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
x_constant = USER.check_constant(x)
method = method.upper()
if method in ['FULL', 'ORD']:
BaseML_Lag.__init__(self, y=y, x=x_constant,
w=w, method=method, epsilon=epsilon)
# increase by 1 to have correct aic and sc, include rho in count
self.k += 1
self.title = "MAXIMUM LIKELIHOOD SPATIAL LAG" + \
" (METHOD = " + method + ")"
self.name_ds = USER.set_name_ds(name_ds)
self.name_y = USER.set_name_y(name_y)
self.name_x = USER.set_name_x(name_x, x)
name_ylag = USER.set_name_yend_sp(self.name_y)
self.name_x.append(name_ylag) # rho changed to last position
self.name_w = USER.set_name_w(name_w, w)
self.aic = DIAG.akaike(reg=self)
self.schwarz = DIAG.schwarz(reg=self)
SUMMARY.ML_Lag(reg=self, w=w, vm=vm, spat_diag=spat_diag)
else:
raise Exception, "{0} is an unsupported method".format(method)
def __init__(self, y, x, w, method='full', epsilon=0.0000001,
spat_diag=False, vm=False, name_y=None, name_x=None,
name_w=None, name_ds=None):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
x_constant = USER.check_constant(x)
method = method.upper()
if method in ['FULL', 'ORD']:
BaseML_Lag.__init__(
self, y=y, x=x_constant, w=w, method=method, epsilon=epsilon)
# increase by 1 to have correct aic and sc, include rho in count
self.k += 1
self.title = "MAXIMUM LIKELIHOOD SPATIAL LAG" + \
" (METHOD = " + method + ")"
self.name_ds = USER.set_name_ds(name_ds)
self.name_y = USER.set_name_y(name_y)
self.name_x = USER.set_name_x(name_x, x)
name_ylag = USER.set_name_yend_sp(self.name_y)
self.name_x.append(name_ylag) # rho changed to last position
self.name_w = USER.set_name_w(name_w, w)
self.aic = DIAG.akaike(reg=self)
self.schwarz = DIAG.schwarz(reg=self)
SUMMARY.ML_Lag(reg=self, w=w, vm=vm, spat_diag=spat_diag)
else:
raise Exception, "{0} is an unsupported method".format(method)
def __init__(self, y, x, yend=None, q=None,\
w=None, w_lags=1, lag_q=True,\
robust=None, gwk=None, sig2n_k=False,\
spat_diag=False,\
vm=False, name_y=None, name_x=None,\
name_yend=None, name_q=None,\
name_w=None, name_gwk=None, name_ds=None):
n = USER.check_arrays(x, yend, q)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
USER.check_robust(robust, gwk)
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
x_constant = USER.check_constant(x)
BaseGM_Lag.__init__(self, y=y, x=x_constant, w=w.sparse, yend=yend2, q=q2,\
w_lags=w_lags, robust=robust, gwk=gwk,\
lag_q=lag_q, sig2n_k=sig2n_k)
self.predy_e, self.e_pred, warn = sp_att(w,self.y,self.predy,\
yend2[:,-1].reshape(self.n,1),self.betas[-1])
set_warn(self, warn)
self.title = "SPATIAL TWO STAGE LEAST SQUARES"
self.name_ds = USER.set_name_ds(name_ds)
self.name_y = USER.set_name_y(name_y)
self.name_x = USER.set_name_x(name_x, x)
self.name_yend = USER.set_name_yend(name_yend, yend)
self.name_yend.append(USER.set_name_yend_sp(self.name_y))
self.name_z = self.name_x + self.name_yend
self.name_q = USER.set_name_q(name_q, q)
self.name_q.extend(
USER.set_name_q_sp(self.name_x, w_lags, self.name_q, lag_q))
self.name_h = USER.set_name_h(self.name_x, self.name_q)
self.robust = USER.set_robust(robust)
self.name_w = USER.set_name_w(name_w, w)
self.name_gwk = USER.set_name_w(name_gwk, gwk)
SUMMARY.GM_Lag(reg=self, w=w, vm=vm, spat_diag=spat_diag)
def __init__(self, y, x, yend=None, q=None,\
w=None, w_lags=1, lag_q=True,\
robust=None, gwk=None, sig2n_k=False,\
spat_diag=False,\
vm=False, name_y=None, name_x=None,\
name_yend=None, name_q=None,\
name_w=None, name_gwk=None, name_ds=None):
n = USER.check_arrays(x, yend, q)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
USER.check_robust(robust, gwk)
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
x_constant = USER.check_constant(x)
BaseGM_Lag.__init__(self, y=y, x=x_constant, w=w.sparse, yend=yend2, q=q2,\
w_lags=w_lags, robust=robust, gwk=gwk,\
lag_q=lag_q, sig2n_k=sig2n_k)
self.predy_e, self.e_pred, warn = sp_att(w,self.y,self.predy,\
yend2[:,-1].reshape(self.n,1),self.betas[-1])
set_warn(self,warn)
self.title = "SPATIAL TWO STAGE LEAST SQUARES"
self.name_ds = USER.set_name_ds(name_ds)
self.name_y = USER.set_name_y(name_y)
self.name_x = USER.set_name_x(name_x, x)
self.name_yend = USER.set_name_yend(name_yend, yend)
self.name_yend.append(USER.set_name_yend_sp(self.name_y))
self.name_z = self.name_x + self.name_yend
self.name_q = USER.set_name_q(name_q, q)
self.name_q.extend(USER.set_name_q_sp(self.name_x, w_lags, self.name_q, lag_q))
self.name_h = USER.set_name_h(self.name_x, self.name_q)
self.robust = USER.set_robust(robust)
self.name_w = USER.set_name_w(name_w, w)
self.name_gwk = USER.set_name_w(name_gwk, gwk)
SUMMARY.GM_Lag(reg=self, w=w, vm=vm, spat_diag=spat_diag)
def __init__(self, y, x, yend=None, q=None,\
w=None, w_lags=1, lag_q=True,\
vm=False, name_y=None, name_x=None,\
name_yend=None, name_q=None,\
name_w=None, name_ds=None):
n = USER.check_arrays(y, x, yend, q)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
x_constant = USER.check_constant(x)
BaseGM_Combo.__init__(self, y=y, x=x_constant, w=w.sparse, yend=yend2, q=q2,\
w_lags=w_lags, lag_q=lag_q)
self.predy_e, self.e_pred, warn = sp_att(w,self.y,\
self.predy,yend2[:,-1].reshape(self.n,1),self.betas[-2])
set_warn(self, warn)
self.title = "SPATIALLY WEIGHTED TWO STAGE LEAST SQUARES"
self.name_ds = USER.set_name_ds(name_ds)
self.name_y = USER.set_name_y(name_y)
self.name_x = USER.set_name_x(name_x, x)
self.name_yend = USER.set_name_yend(name_yend, yend)
self.name_yend.append(USER.set_name_yend_sp(self.name_y))
self.name_z = self.name_x + self.name_yend
self.name_z.append('lambda')
self.name_q = USER.set_name_q(name_q, q)
self.name_q.extend(
USER.set_name_q_sp(self.name_x, w_lags, self.name_q, lag_q))
self.name_h = USER.set_name_h(self.name_x, self.name_q)
self.name_w = USER.set_name_w(name_w, w)
SUMMARY.GM_Combo(reg=self, w=w, vm=vm)
def __init__(self, y, x, yend=None, q=None,\
w=None, w_lags=1, lag_q=True,\
vm=False, name_y=None, name_x=None,\
name_yend=None, name_q=None,\
name_w=None, name_ds=None):
n = USER.check_arrays(y, x, yend, q)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
x_constant = USER.check_constant(x)
BaseGM_Combo.__init__(self, y=y, x=x_constant, w=w.sparse, yend=yend2, q=q2,\
w_lags=w_lags, lag_q=lag_q)
self.rho = self.betas[-2]
self.predy_e, self.e_pred, warn = sp_att(w,self.y,\
self.predy,yend2[:,-1].reshape(self.n,1),self.rho)
set_warn(self, warn)
self.title = "SPATIALLY WEIGHTED TWO STAGE LEAST SQUARES"
self.name_ds = USER.set_name_ds(name_ds)
self.name_y = USER.set_name_y(name_y)
self.name_x = USER.set_name_x(name_x, x)
self.name_yend = USER.set_name_yend(name_yend, yend)
self.name_yend.append(USER.set_name_yend_sp(self.name_y))
self.name_z = self.name_x + self.name_yend
self.name_z.append('lambda')
self.name_q = USER.set_name_q(name_q, q)
self.name_q.extend(USER.set_name_q_sp(self.name_x, w_lags, self.name_q, lag_q))
self.name_h = USER.set_name_h(self.name_x, self.name_q)
self.name_w = USER.set_name_w(name_w, w)
SUMMARY.GM_Combo(reg=self, w=w, vm=vm)
def GM_Lag_Regimes_Multi(self, y, x, w_i, regi_ids, cores=None,\
yend=None, q=None, w_lags=1, lag_q=True,\
robust=None, gwk=None, sig2n_k=False,cols2regi='all',\
spat_diag=False, vm=False, name_y=None, name_x=None,\
name_yend=None, name_q=None, name_regimes=None,\
name_w=None, name_gwk=None, name_ds=None):
pool = mp.Pool(cores)
self.name_ds = USER.set_name_ds(name_ds)
name_x = USER.set_name_x(name_x, x)
name_yend.append(USER.set_name_yend_sp(name_y))
self.name_w = USER.set_name_w(name_w, w_i)
self.name_gwk = USER.set_name_w(name_gwk, gwk)
results_p = {}
for r in self.regimes_set:
w_r = w_i[r].sparse
results_p[r] = pool.apply_async(_work,args=(y,x,regi_ids,r,yend,q,w_r,w_lags,lag_q,robust,sig2n_k,self.name_ds,name_y,name_x,name_yend,name_q,self.name_w,name_regimes, ))
self.kryd = 0
self.kr = len(cols2regi) + 1
self.kf = 0
self.nr = len(self.regimes_set)
self.name_x_r = name_x + name_yend
self.name_regimes = name_regimes
self.vm = np.zeros((self.nr*self.kr,self.nr*self.kr),float)
self.betas = np.zeros((self.nr*self.kr,1),float)
self.u = np.zeros((self.n,1),float)
self.predy = np.zeros((self.n,1),float)
self.predy_e = np.zeros((self.n,1),float)
self.e_pred = np.zeros((self.n,1),float)
pool.close()
pool.join()
results = {}
self.name_y, self.name_x, self.name_yend, self.name_q, self.name_z, self.name_h = [],[],[],[],[],[]
counter = 0
for r in self.regimes_set:
results[r] = results_p[r].get()
results[r].predy_e, results[r].e_pred = sp_att(w_i[r],results[r].y,results[r].predy, results[r].yend[:,-1].reshape(results[r].n,1),results[r].betas[-1])
results[r].w = w_i[r]
self.vm[(counter*self.kr):((counter+1)*self.kr),(counter*self.kr):((counter+1)*self.kr)] = results[r].vm
self.betas[(counter*self.kr):((counter+1)*self.kr),] = results[r].betas
self.u[regi_ids[r],]=results[r].u
self.predy[regi_ids[r],]=results[r].predy
self.predy_e[regi_ids[r],]=results[r].predy_e
self.e_pred[regi_ids[r],]=results[r].e_pred
self.name_y += results[r].name_y
self.name_x += results[r].name_x
self.name_yend += results[r].name_yend
self.name_q += results[r].name_q
self.name_z += results[r].name_z
self.name_h += results[r].name_h
if r == self.regimes_set[0]:
self.hac_var = np.zeros((self.n,results[r].h.shape[1]),float)
self.hac_var[regi_ids[r],] = results[r].h
counter += 1
self.multi = results
if robust == 'hac':
hac_multi(self,gwk,constant=True)
self.chow = REGI.Chow(self)
SUMMARY.GM_Lag_multi(reg=self, multireg=self.multi, vm=vm, spat_diag=spat_diag, regimes=True)
def ML_Lag_Regimes_Multi(self, y, x, w_i, w, regi_ids,\
cores, cols2regi, method, epsilon,\
spat_diag, vm, name_y, name_x,\
name_regimes, name_w, name_ds):
pool = mp.Pool(cores)
name_x = USER.set_name_x(name_x, x)+ [USER.set_name_yend_sp(name_y)]
results_p = {}
for r in self.regimes_set:
if system() == 'Windows':
is_win = True
results_p[r] = _work(*(y,x,regi_ids,r,w_i[r],method,epsilon,name_ds,name_y,name_x,name_w,name_regimes))
else:
results_p[r] = pool.apply_async(_work,args=(y,x,regi_ids,r,w_i[r],method,epsilon,name_ds,name_y,name_x,name_w,name_regimes, ))
is_win = False
self.kryd = 0
self.kr = len(cols2regi) + 1
self.kf = 0
self.nr = len(self.regimes_set)
self.name_x_r = name_x
self.name_regimes = name_regimes
self.vm = np.zeros((self.nr*self.kr,self.nr*self.kr),float)
self.betas = np.zeros((self.nr*self.kr,1),float)
self.u = np.zeros((self.n,1),float)
self.predy = np.zeros((self.n,1),float)
self.predy_e = np.zeros((self.n,1),float)
self.e_pred = np.zeros((self.n,1),float)
if not is_win:
pool.close()
pool.join()
results = {}
self.name_y, self.name_x = [],[]
counter = 0
for r in self.regimes_set:
if is_win:
results[r] = results_p[r]
else:
results[r] = results_p[r].get()
self.vm[(counter*self.kr):((counter+1)*self.kr),(counter*self.kr):((counter+1)*self.kr)] = results[r].vm
self.betas[(counter*self.kr):((counter+1)*self.kr),] = results[r].betas
self.u[regi_ids[r],]=results[r].u
self.predy[regi_ids[r],]=results[r].predy
self.predy_e[regi_ids[r],]=results[r].predy_e
self.e_pred[regi_ids[r],]=results[r].e_pred
self.name_y += results[r].name_y
self.name_x += results[r].name_x
counter += 1
self.multi = results
self.chow = REGI.Chow(self)
SUMMARY.ML_Lag_multi(reg=self, multireg=self.multi, vm=vm, spat_diag=spat_diag, regimes=True, w=w)
def GM_Lag_Regimes_Multi(
self,
y,
x,
w_i,
w,
regi_ids,
cores=False,
yend=None,
q=None,
w_lags=1,
lag_q=True,
robust=None,
gwk=None,
sig2n_k=False,
cols2regi="all",
spat_diag=False,
vm=False,
name_y=None,
name_x=None,
name_yend=None,
name_q=None,
name_regimes=None,
name_w=None,
name_gwk=None,
name_ds=None,
):
# pool = mp.Pool(cores)
self.name_ds = USER.set_name_ds(name_ds)
name_x = USER.set_name_x(name_x, x)
name_yend.append(USER.set_name_yend_sp(name_y))
self.name_w = USER.set_name_w(name_w, w_i)
self.name_gwk = USER.set_name_w(name_gwk, gwk)
results_p = {}
"""
for r in self.regimes_set:
w_r = w_i[r].sparse
if system() == 'Windows':
is_win = True
results_p[r] = _work(*(y,x,regi_ids,r,yend,q,w_r,w_lags,lag_q,robust,sig2n_k,self.name_ds,name_y,name_x,name_yend,name_q,self.name_w,name_regimes))
else:
results_p[r] = pool.apply_async(_work,args=(y,x,regi_ids,r,yend,q,w_r,w_lags,lag_q,robust,sig2n_k,self.name_ds,name_y,name_x,name_yend,name_q,self.name_w,name_regimes, ))
is_win = False
"""
for r in self.regimes_set:
w_r = w_i[r].sparse
if cores:
pool = mp.Pool(None)
results_p[r] = pool.apply_async(
_work,
args=(
y,
x,
regi_ids,
r,
yend,
q,
w_r,
w_lags,
lag_q,
robust,
sig2n_k,
self.name_ds,
name_y,
name_x,
name_yend,
name_q,
self.name_w,
name_regimes,
),
)
else:
results_p[r] = _work(
*(
y,
x,
regi_ids,
r,
yend,
q,
w_r,
w_lags,
lag_q,
robust,
sig2n_k,
self.name_ds,
name_y,
name_x,
name_yend,
name_q,
self.name_w,
name_regimes,
)
)
self.kryd = 0
self.kr = len(cols2regi) + 1
self.kf = 0
self.nr = len(self.regimes_set)
self.name_x_r = name_x + name_yend
self.name_regimes = name_regimes
self.vm = np.zeros((self.nr * self.kr, self.nr * self.kr), float)
self.betas = np.zeros((self.nr * self.kr, 1), float)
self.u = np.zeros((self.n, 1), float)
self.predy = np.zeros((self.n, 1), float)
self.predy_e = np.zeros((self.n, 1), float)
self.e_pred = np.zeros((self.n, 1), float)
"""
if not is_win:
pool.close()
pool.join()
"""
if cores:
pool.close()
pool.join()
results = {}
self.name_y, self.name_x, self.name_yend, self.name_q, self.name_z, self.name_h = [], [], [], [], [], []
counter = 0
for r in self.regimes_set:
"""
if is_win:
results[r] = results_p[r]
else:
results[r] = results_p[r].get()
"""
if not cores:
results[r] = results_p[r]
else:
results[r] = results_p[r].get()
results[r].predy_e, results[r].e_pred, warn = sp_att(
w_i[r], results[r].y, results[r].predy, results[r].yend[:, -1].reshape(results[r].n, 1), results[r].rho
)
set_warn(results[r], warn)
results[r].w = w_i[r]
self.vm[
(counter * self.kr) : ((counter + 1) * self.kr), (counter * self.kr) : ((counter + 1) * self.kr)
] = results[r].vm
self.betas[(counter * self.kr) : ((counter + 1) * self.kr),] = results[r].betas
self.u[regi_ids[r],] = results[r].u
self.predy[regi_ids[r],] = results[r].predy
self.predy_e[regi_ids[r],] = results[r].predy_e
self.e_pred[regi_ids[r],] = results[r].e_pred
self.name_y += results[r].name_y
self.name_x += results[r].name_x
self.name_yend += results[r].name_yend
self.name_q += results[r].name_q
self.name_z += results[r].name_z
self.name_h += results[r].name_h
if r == self.regimes_set[0]:
self.hac_var = np.zeros((self.n, results[r].h.shape[1]), float)
self.hac_var[regi_ids[r],] = results[r].h
counter += 1
self.multi = results
if robust == "hac":
hac_multi(self, gwk, constant=True)
if robust == "ogmm":
set_warn(self, "Residuals treated as homoskedastic for the purpose of diagnostics.")
self.chow = REGI.Chow(self)
if spat_diag:
pass
# self._get_spat_diag_props(y, x, w, yend, q, w_lags, lag_q)
SUMMARY.GM_Lag_multi(reg=self, multireg=self.multi, vm=vm, spat_diag=spat_diag, regimes=True, w=w)
def __init__(
self,
y,
x,
regimes,
yend=None,
q=None,
w=None,
w_lags=1,
lag_q=True,
robust=None,
gwk=None,
sig2n_k=False,
spat_diag=False,
constant_regi="many",
cols2regi="all",
regime_lag_sep=False,
regime_err_sep=True,
cores=False,
vm=False,
name_y=None,
name_x=None,
name_yend=None,
name_q=None,
name_regimes=None,
name_w=None,
name_gwk=None,
name_ds=None,
):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
USER.check_robust(robust, gwk)
USER.check_spat_diag(spat_diag, w)
name_x = USER.set_name_x(name_x, x, constant=True)
name_y = USER.set_name_y(name_y)
name_yend = USER.set_name_yend(name_yend, yend)
name_q = USER.set_name_q(name_q, q)
name_q.extend(USER.set_name_q_sp(name_x, w_lags, name_q, lag_q, force_all=True))
self.name_regimes = USER.set_name_ds(name_regimes)
self.constant_regi = constant_regi
self.n = n
cols2regi = REGI.check_cols2regi(constant_regi, cols2regi, x, yend=yend, add_cons=False)
self.cols2regi = cols2regi
self.regimes_set = REGI._get_regimes_set(regimes)
self.regimes = regimes
USER.check_regimes(self.regimes_set, self.n, x.shape[1])
if regime_err_sep == True and robust == "hac":
set_warn(
self,
"Error by regimes is incompatible with HAC estimation for Spatial Lag models. Hence, error and lag by regimes have been disabled for this model.",
)
regime_err_sep = False
regime_lag_sep = False
self.regime_err_sep = regime_err_sep
self.regime_lag_sep = regime_lag_sep
if regime_lag_sep == True:
if not regime_err_sep:
raise Exception, "regime_err_sep must be True when regime_lag_sep=True."
cols2regi += [True]
w_i, regi_ids, warn = REGI.w_regimes(
w, regimes, self.regimes_set, transform=True, get_ids=True, min_n=len(cols2regi) + 1
)
set_warn(self, warn)
else:
cols2regi += [False]
if regime_err_sep == True and set(cols2regi) == set([True]) and constant_regi == "many":
self.y = y
self.GM_Lag_Regimes_Multi(
y,
x,
w_i,
w,
regi_ids,
yend=yend,
q=q,
w_lags=w_lags,
lag_q=lag_q,
cores=cores,
robust=robust,
gwk=gwk,
sig2n_k=sig2n_k,
cols2regi=cols2regi,
spat_diag=spat_diag,
vm=vm,
name_y=name_y,
name_x=name_x,
name_yend=name_yend,
name_q=name_q,
name_regimes=self.name_regimes,
name_w=name_w,
name_gwk=name_gwk,
name_ds=name_ds,
)
else:
if regime_lag_sep == True:
w = REGI.w_regimes_union(w, w_i, self.regimes_set)
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
name_yend.append(USER.set_name_yend_sp(name_y))
TSLS_Regimes.__init__(
self,
y=y,
x=x,
yend=yend2,
q=q2,
regimes=regimes,
w=w,
robust=robust,
gwk=gwk,
sig2n_k=sig2n_k,
spat_diag=spat_diag,
vm=vm,
constant_regi=constant_regi,
cols2regi=cols2regi,
regime_err_sep=regime_err_sep,
name_y=name_y,
name_x=name_x,
name_yend=name_yend,
name_q=name_q,
name_regimes=name_regimes,
name_w=name_w,
name_gwk=name_gwk,
name_ds=name_ds,
summ=False,
)
if regime_lag_sep:
self.sp_att_reg(w_i, regi_ids, yend2[:, -1].reshape(self.n, 1))
else:
self.rho = self.betas[-1]
self.predy_e, self.e_pred, warn = sp_att(
w, self.y, self.predy, yend2[:, -1].reshape(self.n, 1), self.rho
)
set_warn(self, warn)
self.regime_lag_sep = regime_lag_sep
self.title = "SPATIAL " + self.title
SUMMARY.GM_Lag(reg=self, w=w, vm=vm, spat_diag=spat_diag, regimes=True)
def __init__(self, y, x, regimes, yend=None, q=None,\
w=None, w_lags=1, lag_q=True,\
robust=None, gwk=None, sig2n_k=False,\
spat_diag=False, constant_regi='many',\
cols2regi='all', regime_lag_sep=True, regime_err_sep=True,\
cores=None, vm=False, name_y=None, name_x=None,\
name_yend=None, name_q=None, name_regimes=None,\
name_w=None, name_gwk=None, name_ds=None):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y)
USER.check_robust(robust, gwk)
USER.check_spat_diag(spat_diag, w)
name_x = USER.set_name_x(name_x, x,constant=True)
name_y = USER.set_name_y(name_y)
name_yend = USER.set_name_yend(name_yend, yend)
name_q = USER.set_name_q(name_q, q)
name_q.extend(USER.set_name_q_sp(name_x, w_lags, name_q, lag_q, force_all=True))
self.name_regimes = USER.set_name_ds(name_regimes)
self.constant_regi=constant_regi
self.n = n
if cols2regi == 'all':
if yend!=None:
cols2regi = [True] * (x.shape[1]+yend.shape[1])
else:
cols2regi = [True] * (x.shape[1])
if regime_lag_sep == True:
cols2regi += [True]
self.regimes_set = list(set(regimes))
self.regimes_set.sort()
w_i,regi_ids,warn = REGI.w_regimes(w, regimes, self.regimes_set, transform=True, get_ids=True, min_n=len(cols2regi)+1)
set_warn(self,warn)
if not regime_err_sep:
w = REGI.w_regimes_union(w, w_i, self.regimes_set)
else:
cols2regi += [False]
if regime_err_sep == True:
raise Exception, "All coefficients must vary accross regimes if regime_err_sep = True."
self.cols2regi = cols2regi
if regime_lag_sep == True and regime_err_sep == True:
if set(cols2regi) == set([True]):
self.GM_Lag_Regimes_Multi(y, x, w_i, regi_ids,\
yend=yend, q=q, w_lags=w_lags, lag_q=lag_q, cores=cores,\
robust=robust, gwk=gwk, sig2n_k=sig2n_k, cols2regi=cols2regi,\
spat_diag=spat_diag, vm=vm, name_y=name_y, name_x=name_x,\
name_yend=name_yend, name_q=name_q, name_regimes=self.name_regimes,\
name_w=name_w, name_gwk=name_gwk, name_ds=name_ds)
else:
raise Exception, "All coefficients must vary accross regimes if regime_err_sep = True."
else:
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
name_yend.append(USER.set_name_yend_sp(name_y))
TSLS_Regimes.__init__(self, y=y, x=x, yend=yend2, q=q2,\
regimes=regimes, w=w, robust=robust, gwk=gwk,\
sig2n_k=sig2n_k, spat_diag=spat_diag, vm=vm,\
constant_regi=constant_regi, cols2regi=cols2regi, name_y=name_y,\
name_x=name_x, name_yend=name_yend, name_q=name_q,\
name_regimes=name_regimes, name_w=name_w, name_gwk=name_gwk,\
name_ds=name_ds,summ=False)
if regime_lag_sep:
self.sp_att_reg(w_i, regi_ids, yend2[:,-1].reshape(self.n,1))
else:
self.predy_e, self.e_pred = sp_att(w,self.y,self.predy,\
yend2[:,-1].reshape(self.n,1),self.betas[-1])
self.regime_lag_sep=regime_lag_sep
self.title = "SPATIAL TWO STAGE LEAST SQUARES - REGIMES"
SUMMARY.GM_Lag(reg=self, w=w, vm=vm, spat_diag=spat_diag, regimes=True)
def GM_Lag_Regimes_Multi(self,
y,
x,
w_i,
w,
regi_ids,
cores=False,
yend=None,
q=None,
w_lags=1,
lag_q=True,
robust=None,
gwk=None,
sig2n_k=False,
cols2regi='all',
spat_diag=False,
vm=False,
name_y=None,
name_x=None,
name_yend=None,
name_q=None,
name_regimes=None,
name_w=None,
name_gwk=None,
name_ds=None):
# pool = mp.Pool(cores)
self.name_ds = USER.set_name_ds(name_ds)
name_x = USER.set_name_x(name_x, x)
name_yend.append(USER.set_name_yend_sp(name_y))
self.name_w = USER.set_name_w(name_w, w_i)
self.name_gwk = USER.set_name_w(name_gwk, gwk)
results_p = {}
"""
for r in self.regimes_set:
w_r = w_i[r].sparse
if system() == 'Windows':
is_win = True
results_p[r] = _work(*(y,x,regi_ids,r,yend,q,w_r,w_lags,lag_q,robust,sig2n_k,self.name_ds,name_y,name_x,name_yend,name_q,self.name_w,name_regimes))
else:
results_p[r] = pool.apply_async(_work,args=(y,x,regi_ids,r,yend,q,w_r,w_lags,lag_q,robust,sig2n_k,self.name_ds,name_y,name_x,name_yend,name_q,self.name_w,name_regimes, ))
is_win = False
"""
for r in self.regimes_set:
w_r = w_i[r].sparse
if cores:
pool = mp.Pool(None)
results_p[r] = pool.apply_async(_work,
args=(
y,
x,
regi_ids,
r,
yend,
q,
w_r,
w_lags,
lag_q,
robust,
sig2n_k,
self.name_ds,
name_y,
name_x,
name_yend,
name_q,
self.name_w,
name_regimes,
))
else:
results_p[r] = _work(*(y, x, regi_ids, r, yend, q, w_r, w_lags,
lag_q, robust, sig2n_k, self.name_ds,
name_y, name_x, name_yend, name_q,
self.name_w, name_regimes))
self.kryd = 0
self.kr = len(cols2regi) + 1
self.kf = 0
self.nr = len(self.regimes_set)
self.name_x_r = name_x + name_yend
self.name_regimes = name_regimes
self.vm = np.zeros((self.nr * self.kr, self.nr * self.kr), float)
self.betas = np.zeros((self.nr * self.kr, 1), float)
self.u = np.zeros((self.n, 1), float)
self.predy = np.zeros((self.n, 1), float)
self.predy_e = np.zeros((self.n, 1), float)
self.e_pred = np.zeros((self.n, 1), float)
"""
if not is_win:
pool.close()
pool.join()
"""
if cores:
pool.close()
pool.join()
results = {}
self.name_y, self.name_x, self.name_yend, self.name_q, self.name_z, self.name_h = [
], [], [], [], [], []
counter = 0
for r in self.regimes_set:
"""
if is_win:
results[r] = results_p[r]
else:
results[r] = results_p[r].get()
"""
if not cores:
results[r] = results_p[r]
else:
results[r] = results_p[r].get()
results[r].predy_e, results[r].e_pred, warn = sp_att(
w_i[r], results[r].y, results[r].predy,
results[r].yend[:, -1].reshape(results[r].n,
1), results[r].rho)
set_warn(results[r], warn)
results[r].w = w_i[r]
self.vm[(counter * self.kr):((counter + 1) * self.kr),
(counter * self.kr):((counter + 1) *
self.kr)] = results[r].vm
self.betas[(counter * self.kr):((counter + 1) *
self.kr), ] = results[r].betas
self.u[regi_ids[r], ] = results[r].u
self.predy[regi_ids[r], ] = results[r].predy
self.predy_e[regi_ids[r], ] = results[r].predy_e
self.e_pred[regi_ids[r], ] = results[r].e_pred
self.name_y += results[r].name_y
self.name_x += results[r].name_x
self.name_yend += results[r].name_yend
self.name_q += results[r].name_q
self.name_z += results[r].name_z
self.name_h += results[r].name_h
if r == self.regimes_set[0]:
self.hac_var = np.zeros((self.n, results[r].h.shape[1]), float)
self.hac_var[regi_ids[r], ] = results[r].h
counter += 1
self.multi = results
if robust == 'hac':
hac_multi(self, gwk, constant=True)
if robust == 'ogmm':
set_warn(
self,
"Residuals treated as homoskedastic for the purpose of diagnostics."
)
self.chow = REGI.Chow(self)
if spat_diag:
pass
#self._get_spat_diag_props(y, x, w, yend, q, w_lags, lag_q)
SUMMARY.GM_Lag_multi(reg=self,
multireg=self.multi,
vm=vm,
spat_diag=spat_diag,
regimes=True,
w=w)
def __init__(self,
y,
x,
regimes,
yend=None,
q=None,
w=None,
w_lags=1,
lag_q=True,
robust=None,
gwk=None,
sig2n_k=False,
spat_diag=False,
constant_regi='many',
cols2regi='all',
regime_lag_sep=False,
regime_err_sep=True,
cores=False,
vm=False,
name_y=None,
name_x=None,
name_yend=None,
name_q=None,
name_regimes=None,
name_w=None,
name_gwk=None,
name_ds=None):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
USER.check_robust(robust, gwk)
USER.check_spat_diag(spat_diag, w)
name_x = USER.set_name_x(name_x, x, constant=True)
name_y = USER.set_name_y(name_y)
name_yend = USER.set_name_yend(name_yend, yend)
name_q = USER.set_name_q(name_q, q)
name_q.extend(
USER.set_name_q_sp(name_x, w_lags, name_q, lag_q, force_all=True))
self.name_regimes = USER.set_name_ds(name_regimes)
self.constant_regi = constant_regi
self.n = n
cols2regi = REGI.check_cols2regi(constant_regi,
cols2regi,
x,
yend=yend,
add_cons=False)
self.cols2regi = cols2regi
self.regimes_set = REGI._get_regimes_set(regimes)
self.regimes = regimes
USER.check_regimes(self.regimes_set, self.n, x.shape[1])
if regime_err_sep == True and robust == 'hac':
set_warn(
self,
"Error by regimes is incompatible with HAC estimation for Spatial Lag models. Hence, error and lag by regimes have been disabled for this model."
)
regime_err_sep = False
regime_lag_sep = False
self.regime_err_sep = regime_err_sep
self.regime_lag_sep = regime_lag_sep
if regime_lag_sep == True:
if not regime_err_sep:
raise Exception, "regime_err_sep must be True when regime_lag_sep=True."
cols2regi += [True]
w_i, regi_ids, warn = REGI.w_regimes(w,
regimes,
self.regimes_set,
transform=True,
get_ids=True,
min_n=len(cols2regi) + 1)
set_warn(self, warn)
else:
cols2regi += [False]
if regime_err_sep == True and set(cols2regi) == set(
[True]) and constant_regi == 'many':
self.y = y
self.GM_Lag_Regimes_Multi(y,
x,
w_i,
w,
regi_ids,
yend=yend,
q=q,
w_lags=w_lags,
lag_q=lag_q,
cores=cores,
robust=robust,
gwk=gwk,
sig2n_k=sig2n_k,
cols2regi=cols2regi,
spat_diag=spat_diag,
vm=vm,
name_y=name_y,
name_x=name_x,
name_yend=name_yend,
name_q=name_q,
name_regimes=self.name_regimes,
name_w=name_w,
name_gwk=name_gwk,
name_ds=name_ds)
else:
if regime_lag_sep == True:
w = REGI.w_regimes_union(w, w_i, self.regimes_set)
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
name_yend.append(USER.set_name_yend_sp(name_y))
TSLS_Regimes.__init__(self,
y=y,
x=x,
yend=yend2,
q=q2,
regimes=regimes,
w=w,
robust=robust,
gwk=gwk,
sig2n_k=sig2n_k,
spat_diag=spat_diag,
vm=vm,
constant_regi=constant_regi,
cols2regi=cols2regi,
regime_err_sep=regime_err_sep,
name_y=name_y,
name_x=name_x,
name_yend=name_yend,
name_q=name_q,
name_regimes=name_regimes,
name_w=name_w,
name_gwk=name_gwk,
name_ds=name_ds,
summ=False)
if regime_lag_sep:
self.sp_att_reg(w_i, regi_ids, yend2[:, -1].reshape(self.n, 1))
else:
self.rho = self.betas[-1]
self.predy_e, self.e_pred, warn = sp_att(
w, self.y, self.predy, yend2[:, -1].reshape(self.n, 1),
self.rho)
set_warn(self, warn)
self.regime_lag_sep = regime_lag_sep
self.title = "SPATIAL " + self.title
SUMMARY.GM_Lag(reg=self,
w=w,
vm=vm,
spat_diag=spat_diag,
regimes=True)
def __init__(self, y, x, regimes, yend=None, q=None,\
w=None, w_lags=1, lag_q=True,\
robust=None, gwk=None, sig2n_k=False,\
spat_diag=False, constant_regi='many',\
cols2regi='all', regime_lag_sep=False, regime_err_sep=True,\
cores=None, vm=False, name_y=None, name_x=None,\
name_yend=None, name_q=None, name_regimes=None,\
name_w=None, name_gwk=None, name_ds=None):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
USER.check_robust(robust, gwk)
USER.check_spat_diag(spat_diag, w)
name_x = USER.set_name_x(name_x, x, constant=True)
name_y = USER.set_name_y(name_y)
name_yend = USER.set_name_yend(name_yend, yend)
name_q = USER.set_name_q(name_q, q)
name_q.extend(
USER.set_name_q_sp(name_x, w_lags, name_q, lag_q, force_all=True))
self.name_regimes = USER.set_name_ds(name_regimes)
self.constant_regi = constant_regi
self.n = n
cols2regi = REGI.check_cols2regi(constant_regi,
cols2regi,
x,
yend=yend,
add_cons=False)
self.cols2regi = cols2regi
self.regimes_set = REGI._get_regimes_set(regimes)
self.regimes = regimes
USER.check_regimes(self.regimes_set)
self.regime_err_sep = regime_err_sep
self.regime_lag_sep = regime_lag_sep
if regime_lag_sep == True:
if not regime_err_sep:
raise Exception, "regime_err_sep must be True when regime_lag_sep=True."
cols2regi += [True]
w_i, regi_ids, warn = REGI.w_regimes(w,
regimes,
self.regimes_set,
transform=True,
get_ids=True,
min_n=len(cols2regi) + 1)
set_warn(self, warn)
else:
cols2regi += [False]
if regime_err_sep == True and set(cols2regi) == set(
[True]) and constant_regi == 'many':
self.y = y
self.GM_Lag_Regimes_Multi(y, x, w_i, regi_ids,\
yend=yend, q=q, w_lags=w_lags, lag_q=lag_q, cores=cores,\
robust=robust, gwk=gwk, sig2n_k=sig2n_k, cols2regi=cols2regi,\
spat_diag=spat_diag, vm=vm, name_y=name_y, name_x=name_x,\
name_yend=name_yend, name_q=name_q, name_regimes=self.name_regimes,\
name_w=name_w, name_gwk=name_gwk, name_ds=name_ds)
else:
if regime_lag_sep == True:
w = REGI.w_regimes_union(w, w_i, self.regimes_set)
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
name_yend.append(USER.set_name_yend_sp(name_y))
TSLS_Regimes.__init__(self, y=y, x=x, yend=yend2, q=q2,\
regimes=regimes, w=w, robust=robust, gwk=gwk,\
sig2n_k=sig2n_k, spat_diag=spat_diag, vm=vm,\
constant_regi=constant_regi, cols2regi=cols2regi, regime_err_sep=regime_err_sep,\
name_y=name_y, name_x=name_x, name_yend=name_yend, name_q=name_q,\
name_regimes=name_regimes, name_w=name_w, name_gwk=name_gwk,\
name_ds=name_ds,summ=False)
if regime_lag_sep:
self.sp_att_reg(w_i, regi_ids, yend2[:, -1].reshape(self.n, 1))
else:
self.predy_e, self.e_pred, warn = sp_att(w,self.y,self.predy,\
yend2[:,-1].reshape(self.n,1),self.betas[-1])
set_warn(self, warn)
self.regime_lag_sep = regime_lag_sep
if regime_err_sep == True:
self.title = "SPATIAL TWO STAGE LEAST SQUARES - REGIMES (Group-wise heteroskedasticity)"
else:
self.title = "SPATIAL TWO STAGE LEAST SQUARES - REGIMES"
SUMMARY.GM_Lag(reg=self,
w=w,
vm=vm,
spat_diag=spat_diag,
regimes=True)
def ML_Lag_Regimes_Multi(self, y, x, w_i, w, regi_ids,
cores, cols2regi, method, epsilon,
spat_diag, vm, name_y, name_x,
name_regimes, name_w, name_ds):
# pool = mp.Pool(cores)
name_x = USER.set_name_x(name_x, x) + [USER.set_name_yend_sp(name_y)]
results_p = {}
"""
for r in self.regimes_set:
if system() == 'Windows':
is_win = True
results_p[r] = _work(*(y,x,regi_ids,r,w_i[r],method,epsilon,name_ds,name_y,name_x,name_w,name_regimes))
else:
results_p[r] = pool.apply_async(_work,args=(y,x,regi_ids,r,w_i[r],method,epsilon,name_ds,name_y,name_x,name_w,name_regimes, ))
is_win = False
"""
for r in self.regimes_set:
if cores:
pool = mp.Pool(None)
results_p[r] = pool.apply_async(_work, args=(y, x, regi_ids, r, w_i[
r], method, epsilon, name_ds, name_y, name_x, name_w, name_regimes, ))
else:
results_p[r] = _work(
*(y, x, regi_ids, r, w_i[r], method, epsilon, name_ds, name_y, name_x, name_w, name_regimes))
self.kryd = 0
self.kr = len(cols2regi) + 1
self.kf = 0
self.nr = len(self.regimes_set)
self.name_x_r = name_x
self.name_regimes = name_regimes
self.vm = np.zeros((self.nr * self.kr, self.nr * self.kr), float)
self.betas = np.zeros((self.nr * self.kr, 1), float)
self.u = np.zeros((self.n, 1), float)
self.predy = np.zeros((self.n, 1), float)
self.predy_e = np.zeros((self.n, 1), float)
self.e_pred = np.zeros((self.n, 1), float)
"""
if not is_win:
pool.close()
pool.join()
"""
if cores:
pool.close()
pool.join()
results = {}
self.name_y, self.name_x = [], []
counter = 0
for r in self.regimes_set:
"""
if is_win:
results[r] = results_p[r]
else:
results[r] = results_p[r].get()
"""
if not cores:
results[r] = results_p[r]
else:
results[r] = results_p[r].get()
self.vm[(counter * self.kr):((counter + 1) * self.kr),
(counter * self.kr):((counter + 1) * self.kr)] = results[r].vm
self.betas[
(counter * self.kr):((counter + 1) * self.kr), ] = results[r].betas
self.u[regi_ids[r], ] = results[r].u
self.predy[regi_ids[r], ] = results[r].predy
self.predy_e[regi_ids[r], ] = results[r].predy_e
self.e_pred[regi_ids[r], ] = results[r].e_pred
self.name_y += results[r].name_y
self.name_x += results[r].name_x
counter += 1
self.multi = results
self.chow = REGI.Chow(self)
SUMMARY.ML_Lag_multi(
reg=self, multireg=self.multi, vm=vm, spat_diag=spat_diag, regimes=True, w=w)
def __init__(self, y, x, regimes, w=None, constant_regi='many',
cols2regi='all', method='full', epsilon=0.0000001,
regime_lag_sep=False, regime_err_sep=False, cores=False, spat_diag=False,
vm=False, name_y=None, name_x=None,
name_w=None, name_ds=None, name_regimes=None):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
USER.check_spat_diag(spat_diag, w)
name_y = USER.set_name_y(name_y)
self.name_y = name_y
self.name_x_r = USER.set_name_x(
name_x, x) + [USER.set_name_yend_sp(name_y)]
self.method = method
self.epsilon = epsilon
self.name_regimes = USER.set_name_ds(name_regimes)
self.constant_regi = constant_regi
self.n = n
cols2regi = REGI.check_cols2regi(
constant_regi, cols2regi, x, add_cons=False)
self.cols2regi = cols2regi
self.regimes_set = REGI._get_regimes_set(regimes)
self.regimes = regimes
self.regime_lag_sep = regime_lag_sep
self._cache = {}
self.name_ds = USER.set_name_ds(name_ds)
self.name_w = USER.set_name_w(name_w, w)
USER.check_regimes(self.regimes_set, self.n, x.shape[1])
# regime_err_sep is ignored, always False
if regime_lag_sep == True:
if not (set(cols2regi) == set([True]) and constant_regi == 'many'):
raise Exception, "All variables must vary by regimes if regime_lag_sep = True."
cols2regi += [True]
w_i, regi_ids, warn = REGI.w_regimes(
w, regimes, self.regimes_set, transform=True, get_ids=True, min_n=len(cols2regi) + 1)
set_warn(self, warn)
else:
cols2regi += [False]
if set(cols2regi) == set([True]) and constant_regi == 'many':
self.y = y
self.ML_Lag_Regimes_Multi(y, x, w_i, w, regi_ids,
cores=cores, cols2regi=cols2regi, method=method, epsilon=epsilon,
spat_diag=spat_diag, vm=vm, name_y=name_y, name_x=name_x,
name_regimes=self.name_regimes,
name_w=name_w, name_ds=name_ds)
else:
# if regime_lag_sep == True:
# w = REGI.w_regimes_union(w, w_i, self.regimes_set)
name_x = USER.set_name_x(name_x, x, constant=True)
x, self.name_x = REGI.Regimes_Frame.__init__(self, x,
regimes, constant_regi, cols2regi=cols2regi[:-1], names=name_x)
self.name_x.append("_Global_" + USER.set_name_yend_sp(name_y))
BaseML_Lag.__init__(
self, y=y, x=x, w=w, method=method, epsilon=epsilon)
self.kf += 1 # Adding a fixed k to account for spatial lag in Chow
# adding a fixed k to account for spatial lag in aic, sc
self.k += 1
self.chow = REGI.Chow(self)
self.aic = DIAG.akaike(reg=self)
self.schwarz = DIAG.schwarz(reg=self)
self.regime_lag_sep = regime_lag_sep
self.title = "MAXIMUM LIKELIHOOD SPATIAL LAG - REGIMES" + \
" (METHOD = " + method + ")"
SUMMARY.ML_Lag(
reg=self, w=w, vm=vm, spat_diag=spat_diag, regimes=True)
def __init__(self, y, x, regimes, yend=None, q=None,\
w=None, w_lags=1, lag_q=True,\
robust=None, gwk=None, sig2n_k=False,\
spat_diag=False, constant_regi='many',\
cols2regi='all', regime_lag_sep=False, regime_err_sep=True,\
cores=None, vm=False, name_y=None, name_x=None,\
name_yend=None, name_q=None, name_regimes=None,\
name_w=None, name_gwk=None, name_ds=None):
n = USER.check_arrays(y, x)
USER.check_y(y, n)
USER.check_weights(w, y, w_required=True)
USER.check_robust(robust, gwk)
USER.check_spat_diag(spat_diag, w)
name_x = USER.set_name_x(name_x, x,constant=True)
name_y = USER.set_name_y(name_y)
name_yend = USER.set_name_yend(name_yend, yend)
name_q = USER.set_name_q(name_q, q)
name_q.extend(USER.set_name_q_sp(name_x, w_lags, name_q, lag_q, force_all=True))
self.name_regimes = USER.set_name_ds(name_regimes)
self.constant_regi=constant_regi
self.n = n
cols2regi = REGI.check_cols2regi(constant_regi, cols2regi, x, yend=yend, add_cons=False)
self.cols2regi = cols2regi
self.regimes_set = REGI._get_regimes_set(regimes)
self.regimes = regimes
USER.check_regimes(self.regimes_set)
self.regime_err_sep = regime_err_sep
self.regime_lag_sep = regime_lag_sep
if regime_lag_sep == True:
if not regime_err_sep:
raise Exception, "regime_err_sep must be True when regime_lag_sep=True."
cols2regi += [True]
w_i,regi_ids,warn = REGI.w_regimes(w, regimes, self.regimes_set, transform=True, get_ids=True, min_n=len(cols2regi)+1)
set_warn(self,warn)
else:
cols2regi += [False]
if regime_err_sep == True and set(cols2regi) == set([True]) and constant_regi == 'many':
self.y = y
self.GM_Lag_Regimes_Multi(y, x, w_i, regi_ids,\
yend=yend, q=q, w_lags=w_lags, lag_q=lag_q, cores=cores,\
robust=robust, gwk=gwk, sig2n_k=sig2n_k, cols2regi=cols2regi,\
spat_diag=spat_diag, vm=vm, name_y=name_y, name_x=name_x,\
name_yend=name_yend, name_q=name_q, name_regimes=self.name_regimes,\
name_w=name_w, name_gwk=name_gwk, name_ds=name_ds)
else:
if regime_lag_sep == True:
w = REGI.w_regimes_union(w, w_i, self.regimes_set)
yend2, q2 = set_endog(y, x, w, yend, q, w_lags, lag_q)
name_yend.append(USER.set_name_yend_sp(name_y))
TSLS_Regimes.__init__(self, y=y, x=x, yend=yend2, q=q2,\
regimes=regimes, w=w, robust=robust, gwk=gwk,\
sig2n_k=sig2n_k, spat_diag=spat_diag, vm=vm,\
constant_regi=constant_regi, cols2regi=cols2regi, regime_err_sep=regime_err_sep,\
name_y=name_y, name_x=name_x, name_yend=name_yend, name_q=name_q,\
name_regimes=name_regimes, name_w=name_w, name_gwk=name_gwk,\
name_ds=name_ds,summ=False)
if regime_lag_sep:
self.sp_att_reg(w_i, regi_ids, yend2[:,-1].reshape(self.n,1))
else:
self.predy_e, self.e_pred, warn = sp_att(w,self.y,self.predy,\
yend2[:,-1].reshape(self.n,1),self.betas[-1])
set_warn(self,warn)
self.regime_lag_sep=regime_lag_sep
if regime_err_sep == True:
self.title = "SPATIAL TWO STAGE LEAST SQUARES - REGIMES (Group-wise heteroskedasticity)"
else:
self.title = "SPATIAL TWO STAGE LEAST SQUARES - REGIMES"
SUMMARY.GM_Lag(reg=self, w=w, vm=vm, spat_diag=spat_diag, regimes=True)