示例#1
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 def __init__(self, df, y_name, x_name, z_name, w_name, **kwargs):
     super(IVReg, self).__init__(df, y_name, x_name, **kwargs)
     # Handle extra variable stuff for IV
     self.z_name = force_list(z_name)
     self.w_name = force_list(w_name)
     self.sample_cols_labels += ('z_name', 'w_name')
     self.sample_store_labels += ('z', 'w')
     self.vars_in_reg += ('z', 'w')
     self.add_constant_to = 'w'
示例#2
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def flag_sample(df, *args):
    varlist = []
    for var in args:
        if var is not None:
            varlist += force_list(var)
    sample = df[varlist].notnull().all(axis=1)
    return sample
示例#3
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    def __init__(self, df, y_name, x_name, **kwargs):
        self.df = df
        self.y_name = y_name
        self.__dict__.update(kwargs)

        self.sample_cols_labels = (
            'y_name', 'x_name', 'fe_name', 'cluster', 'shac_x', 'shac_y',
            'awt_name'
        )

        self.sample_store_labels = (
            'y', 'x', 'A', 'cluster_id', 'shac_x', 'shac_y', 'AWT'
        )

        self.vars_in_reg = ('y', 'x')
        self.add_constant_to = 'x'

        # Set `vce_type`
        self.vce_type = _set_vce_type(self.vce_type, self.cluster, self.shac)
        # Unpack spatial HAC args
        sp_args = unpack_shac_args(self.shac)
        self.shac_x = sp_args[0]
        self.shac_y = sp_args[1]
        self.shac_band = sp_args[2]
        self.shac_kern = sp_args[3]

        # Force variable names to lists
        self.x_name = force_list(x_name)
示例#4
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    def Ftest(self, col_names, equal=False):
        """F test using regression results.

        Args:
            col_names (str or list): Regressor name(s) to test.

        Keyword Args:
            equal (bool): Defaults to False. If True, test if all coefficients
                in ``col_names`` are equal. If False, test if ``col_names`` are
                jointly significant.

        Returns:
            tuple: A tuple containing:
                - **F** (float): F-stat.
                - **pF** (float): p-score for ``F``.
        """
        cols = force_list(col_names)
        V = self.vce.loc[cols, cols]
        q = len(cols)
        beta = self.beta.loc[cols]

        if equal:
            q -= 1
            R = np.zeros((q, q+1))
            for i in range(q):
                R[i, i] = 1
                R[i, i+1] = -1
        else:
            R = np.eye(q)

        r = np.zeros(q)

        return f_test(V, R, beta, r, self.df_r)
 def test_string(self):
     a_string = 'abcd'
     expected = [a_string]
     result = force_list(a_string)
     assert expected == result
 def test_series(self):
     a_series = pd.Series(np.arange(3))
     expected = a_series.tolist()
     result = force_list(a_series)
     assert expected == result
 def test_array(self):
     an_array = np.arange(3)
     expected = an_array.tolist()
     result = force_list(an_array)
     assert expected == result
 def test_tup(self):
     a_tuple = (1, 2, 3)
     expected = list(a_tuple)
     result = force_list(a_tuple)
     assert expected == result
 def test_int(self):
     an_int = 10
     expected = [an_int]
     result = force_list(an_int)
     assert expected == result
 def test_list(self):
     expected = [1, 2, 3]
     result = force_list(expected)
     assert expected == result