arch.unitroot.cointegration.DynamicOLSResults

class arch.unitroot.cointegration.DynamicOLSResults(params, cov, resid, lags, leads, cov_type, kernel_est, num_x, trend, reg_results, df_adjust)[source]

Estimation results for Dynamic OLS models

Parameters
  • params (Series) – The estimated model parameters.

  • cov (DataFrame) – The estimated parameter covariance.

  • resid (Series) – The model residuals.

  • lags (int) – The number of lags included in the model.

  • leads (int) – The number of leads included in the model.

  • cov_type (str) – The type of the parameter covariance estimator used.

  • kernel_est (CovarianceEstimator) – The covariance estimator instance used to estimate the parameter covariance.

  • reg_results (RegressionResults) – Regression results from fitting statsmodels OLS.

  • df_adjust (bool) – Whether to degree of freedom adjust the estimator.

Methods

summary([full])

Summary of the model, containing estimated parameters and std.

Properties

bandwidth

The bandwidth used in the parameter covariance estimation

cov

The estimated parameter covariance of the cointegrating vector

cov_type

The type of parameter covariance estimator used

full_cov

Parameter covariance of the all model parameters, incl.

full_params

The complete set of parameters, including leads and lags

kernel

The kernel used to estimate the covariance

lags

The number of lags included in the model

leads

The number of leads included in the model

long_run_variance

The long-run variance of the regression residual.

params

The estimated parameters of the cointegrating vector

pvalues

P-value of the parameters in the cointegrating vector

resid

The model residuals

residual_variance

The variance of the regression residual.

rsquared

The model R²

rsquared_adj

The degree-of-freedom adjusted R²

std_errors

Standard errors of the parameters in the cointegrating vector

tvalues

T-statistics of the parameters in the cointegrating vector