# The default method for the fit is Newton-Raphson
# However, you can use other solvers
mlogit_res = mlogit_mod.fit(method='bfgs', maxiter=100)
# The below needs a lot of iterations to get it right?
#TODO: Add a technical note on algorithms
#mlogit_res = mlogit_mod.fit(method='ncg') # this takes forever
from statsmodels.iolib.summary import (
summary_params_2d, summary_params_2dflat)
exog_names = [anes_data.exog_name[i] for i in [0, 2]+range(5,8)] + ['const']
endog_names = [anes_data.endog_name+'_%d' % i for i in np.unique(mlogit_res.model.endog)[1:]]
print '\n\nMultinomial'
print summary_params_2d(mlogit_res, extras=['bse','tvalues'],
endog_names=endog_names, exog_names=exog_names)
tables, table_all = summary_params_2dflat(mlogit_res,
endog_names=endog_names,
exog_names=exog_names,
keep_headers=True)
tables, table_all = summary_params_2dflat(mlogit_res,
endog_names=endog_names,
exog_names=exog_names,
keep_headers=False)
print '\n\n'
print table_all
print '\n\n'
print '\n'.join((str(t) for t in tables))
from statsmodels.iolib.summary import table_extend
at = table_extend(tables)
mlogit_res = mlogit_mod.fit(method='bfgs', maxiter=100)
# The below needs a lot of iterations to get it right?
#TODO: Add a technical note on algorithms
#mlogit_res = mlogit_mod.fit(method='ncg') # this takes forever
from statsmodels.iolib.summary import (summary_params_2d,
summary_params_2dflat)
exog_names = [anes_data.exog_name[i] for i in [0, 2] + range(5, 8)] + ['const']
endog_names = [
anes_data.endog_name + '_%d' % i
for i in np.unique(mlogit_res.model.endog)[1:]
]
print '\n\nMultinomial'
print summary_params_2d(mlogit_res,
extras=['bse', 'tvalues'],
endog_names=endog_names,
exog_names=exog_names)
tables, table_all = summary_params_2dflat(mlogit_res,
endog_names=endog_names,
exog_names=exog_names,
keep_headers=True)
tables, table_all = summary_params_2dflat(mlogit_res,
endog_names=endog_names,
exog_names=exog_names,
keep_headers=False)
print '\n\n'
print table_all
print '\n\n'
print '\n'.join((str(t) for t in tables))
from statsmodels.iolib.summary import table_extend