def f_stat(self):
"""Returns the f-stat value."""
f_stat_dicts = dict(
(date, common.f_stat_to_dict(f_stat))
for date, f_stat in zip(self.beta.index, self._f_stat_raw))
return DataFrame(f_stat_dicts).T
def f_stat(self):
"""Returns the f-stat value."""
f_stat_dicts = dict((date, common.f_stat_to_dict(f_stat))
for date, f_stat in zip(self.beta.index,
self._f_stat_raw))
return DataFrame(f_stat_dicts).T
def f_test(self, hypothesis):
"""Runs the F test, given a joint hypothesis. The hypothesis is
represented by a collection of equations, in the form
A*x_1+B*x_2=C
You must provide the coefficients even if they're 1. No spaces.
The equations can be passed as either a single string or a
list of strings.
Examples
--------
o = ols(...)
o.f_test('1*x1+2*x2=0,1*x3=0')
o.f_test(['1*x1+2*x2=0','1*x3=0'])
"""
x_names = self._x.columns
R = []
r = []
if isinstance(hypothesis, str):
eqs = hypothesis.split(',')
elif isinstance(hypothesis, list):
eqs = hypothesis
else: # pragma: no cover
raise Exception('hypothesis must be either string or list')
for equation in eqs:
row = np.zeros(len(x_names))
lhs, rhs = equation.split('=')
for s in lhs.split('+'):
ss = s.split('*')
coeff = float(ss[0])
x_name = ss[1]
if x_name not in x_names:
raise Exception('no coefficient named %s' % x_name)
idx = x_names.get_loc(x_name)
row[idx] = coeff
rhs = float(rhs)
R.append(row)
r.append(rhs)
R = np.array(R)
q = len(r)
r = np.array(r).reshape(q, 1)
result = math.calc_F(R, r, self._beta_raw, self._var_beta_raw,
self._nobs, self.df)
return common.f_stat_to_dict(result)
def f_test(self, hypothesis):
"""Runs the F test, given a joint hypothesis. The hypothesis is
represented by a collection of equations, in the form
A*x_1+B*x_2=C
You must provide the coefficients even if they're 1. No spaces.
The equations can be passed as either a single string or a
list of strings.
Examples
--------
o = ols(...)
o.f_test('1*x1+2*x2=0,1*x3=0')
o.f_test(['1*x1+2*x2=0','1*x3=0'])
"""
x_names = self._x.columns
R = []
r = []
if isinstance(hypothesis, str):
eqs = hypothesis.split(',')
elif isinstance(hypothesis, list):
eqs = hypothesis
else:
raise Exception('hypothesis must be either string or list')
for equation in eqs:
row = np.zeros(len(x_names))
lhs, rhs = equation.split('=')
for s in lhs.split('+'):
ss = s.split('*')
coeff = float(ss[0])
x_name = ss[1]
idx = x_names.indexMap[x_name]
row[idx] = coeff
rhs = float(rhs)
R.append(row)
r.append(rhs)
R = np.array(R)
q = len(r)
r = np.array(r).reshape(q, 1)
result = math.calc_F(R, r, self._beta_raw, self._var_beta_raw,
self._nobs, self.df)
return common.f_stat_to_dict(result)
def f_stat(self):
"""Returns the f-stat value."""
return common.f_stat_to_dict(self._f_stat_raw)
def f_stat(self):
"""Returns the f-stat value."""
return common.f_stat_to_dict(self._f_stat_raw)
