def _r_tobit(self, data, xvars, rbar):
""" Estimate tobit with function from r """
r.assign('data', com.convert_to_r_dataframe(data))
rhs = '+'.join(xvars)
model = r("vglm(OverallRank ~ "+ rhs +", \
family=tobit(Upper=" + str(rbar) + ", Lower=1), \
data=data, crit='coeff')")
if self.opts['verbose']:
print(r.summary(model))
out = r.coef(model, matrix=True)
out = np.array(out)
index = deepcopy(xvars)
index.insert(0, 'const')
beta = pd.Series(out[:, 0], index=index)
return {'beta': beta, 'sigma': out[0, 1]}
def beta(self):
return rpy.convert_robj(r.coef(self._estimate))
def beta(self):
return rpy.convert_robj(r.coef(self._estimate))
