estimation.quantreg.quantreg_.Quantreg
estimation.quantreg.quantreg_.Quantreg(
FixestFormula,
data,
ssc_dict,
drop_singletons,
drop_intercept,
weights,
weights_type,
collin_tol,
fixef_tol,
fixef_maxiter,
lookup_demeaned_data,
solver='np.linalg.solve',
demeaner_backend='numba',
store_data=True,
copy_data=True,
lean=False,
context=0,
sample_split_var=None,
sample_split_value=None,
quantile=0.5,
method='fn',
quantile_tol=1e-06,
quantile_maxiter=None,
seed=None,
)Quantile regression model.
Attributes
| Name | Description |
|---|---|
| objective_value | Compute the total loss of the quantile regression model. |
Methods
| Name | Description |
|---|---|
| fit_qreg_fn | Fit a quantile regression model using the Frisch-Newton Interior Point Solver. |
| fit_qreg_pfn | Fit a quantile regression model using the Frisch-Newton Interior Point Solver with pre-processing. |
| get_fit | Fit a quantile regression model using the interior point method. |
| get_performance | Compute performance metrics for the quantile regression model. |
| prepare_model_matrix | Prepare model inputs for estimation. |
| to_array | Turn estimation DataFrames to np arrays. |
fit_qreg_fn
estimation.quantreg.quantreg_.Quantreg.fit_qreg_fn(
X,
Y,
q,
tol=None,
maxiter=None,
beta_init=None,
)Fit a quantile regression model using the Frisch-Newton Interior Point Solver.
fit_qreg_pfn
estimation.quantreg.quantreg_.Quantreg.fit_qreg_pfn(
X,
Y,
q,
m=None,
tol=None,
maxiter=None,
beta_init=None,
rng=None,
eta=None,
)Fit a quantile regression model using the Frisch-Newton Interior Point Solver with pre-processing.
get_fit
estimation.quantreg.quantreg_.Quantreg.get_fit()Fit a quantile regression model using the interior point method.
get_performance
estimation.quantreg.quantreg_.Quantreg.get_performance()Compute performance metrics for the quantile regression model.
prepare_model_matrix
estimation.quantreg.quantreg_.Quantreg.prepare_model_matrix()Prepare model inputs for estimation.
to_array
estimation.quantreg.quantreg_.Quantreg.to_array()Turn estimation DataFrames to np arrays.