def lm_fit(self, output_label, model_fun, x_column_or_label=None):
if x_column_or_label is None:
input_labels = [
lbl for lbl in self.labels if not lbl == output_label
]
f_values = [
model_fun(*row) for row in self.select(input_labels).rows
]
p = len(input_labels)
else:
f_values = model_fun(self._get_column(x_column_or_label))
p = 1
fit_tbl = Table(["Quantity", "Value"])
return fit_tbl.with_rows([
("Residual standard error", self.RSE(output_label, f_values)),
("R^2", self.R2(output_label, f_values)),
("F-statistic", self.F_stat(output_label, f_values, p))
])
def with_rows(self, *args, **kwargs):
return self._fix_(Table.with_rows(*args, **kwargs))
