Beispiel #1
0
    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
Beispiel #2
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    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
Beispiel #3
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    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)
Beispiel #4
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    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)
Beispiel #5
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 def f_stat(self):
     """Returns the f-stat value."""
     return common.f_stat_to_dict(self._f_stat_raw)
Beispiel #6
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 def f_stat(self):
     """Returns the f-stat value."""
     return common.f_stat_to_dict(self._f_stat_raw)