str = 'robust', debiased: bool = True, **cov_config: str | float) LinearFactorModelResults[source]

Estimate model parameters

cov_type: str = 'robust'

Name of covariance estimator

debiased: bool = True

Flag indicating whether to debias the covariance estimator using a degree of freedom adjustment

**cov_config : dict

Additional covariance-specific options. See Notes.


Results class with parameter estimates, covariance and test statistics

Return type:



Supported covariance estimators are:

  • “robust” - Heteroskedasticity-robust covariance estimator

  • “kernel” - Heteroskedasticity and Autocorrelation consistent (HAC) covariance estimator

The kernel covariance estimator takes the optional arguments kernel, one of “bartlett”, “parzen” or “qs” (quadratic spectral) and bandwidth (a positive integer).