statsmodels.regression.process_regression.ProcessMLEResults.covariance

ProcessMLEResults.covariance(time, scale, smooth)[source]

Returns a fitted covariance matrix.

Parameters:
timearray_like

The time points at which the fitted covariance matrix is calculated.

scalearray_like

The data used to determine the scale parameter, must have len(time) rows.

smootharray_like

The data used to determine the smoothness parameter, must have len(time) rows.

Returns:
A covariance matrix.

Notes

If the model was fit using formulas, scale and smooth should be Dataframes, containing all variables that were present in the respective scaling and smoothing formulas used to fit the model. Otherwise, scale and smooth should be data arrays whose columns align with the fitted scaling and smoothing parameters.


Last update: Jun 14, 2024