FunctionalVARResult.fitted_curves#

FunctionalVARResult.fitted_curves()[source]#

One-step conditional mean curves over the factor VAR’s effective sample.

Return type:

NDArray[double]

Returns:

An (nobs - p, n_points) array, the factor VAR’s fitted values mapped through the basis.

Example

>>> import numpy as np
>>> rng = np.random.default_rng(0)
>>> grid = np.linspace(0.0, 1.0, 25)
>>> curves = 0.1 * np.cumsum(rng.standard_normal(80))[:, None] + np.sin(np.pi * grid)
>>> res = FunctionalVAR(curves, grid, order=1).fit()
>>> fitted = res.fitted_curves()
>>> expected = res.mean_curve + res.factors.fittedvalues @ res.basis_matrix.T
>>> fitted.shape, bool(np.allclose(fitted, expected))
((79, 25), True)