linearmodels.iv.absorbing.AbsorbingLSResults¶

class linearmodels.iv.absorbing.AbsorbingLSResults(results: dict[str, Any], model: AbsorbingLS)[source]¶

Results from the estimation of a model with absorbed effects.

Parameters:¶

results: dict[str, Any]¶

A dictionary of results from the model estimation.

model: AbsorbingLS¶

The model used to estimate parameters.

Methods

conf_int([level])	Confidence interval construction.
wald_test([restriction, value, formula])	Test linear equality constraints using a Wald test.

Properties

absorbed_effects	Fitted values from only absorbed terms.
absorbed_rsquared	Coefficient of determination (R**2), ignoring absorbed variables.
cov	Estimated covariance of parameters.
cov_config	Parameter values from covariance estimator.
cov_estimator	Type of covariance estimator used to compute covariance.
cov_type	Covariance estimator used.
debiased	Flag indicating whether covariance uses a small-sample adjustment.
df_absorbed	Number of variables absorbed.
df_model	Model degree of freedom.
df_resid	Residual degree of freedom.
f_statistic	Model F-statistic.
fitted_values	Fitted values.
has_constant	Flag indicating the model includes a constant or equivalent.
idiosyncratic	Idiosyncratic error.
method	Method used to estimate model parameters.
model_ss	Model sum of squares.
nobs	Number of observations.
params	Estimated parameters.
pvalues	Parameter p-values.
resid_ss	Residual sum of squares.
resids	Estimated residuals.
rsquared	Coefficient of determination (R**2).
rsquared_adj	Sample-size adjusted coefficient of determination (R**2).
s2	Residual variance estimator.
std_errors	Estimated parameter standard errors.
summary	Model estimation summary.
total_ss	Total sum of squares.
tstats	Parameter t-statistics.
wresids	Weighted estimated residuals.