FactorSVResult.loadings

property FactorSVResult.loadings: NDArray[float64]

Posterior-mean loading matrix, (k, r).

Lower triangular with a unit diagonal in the leading r rows by construction; those cells have no posterior spread.

Example

>>> import numpy as np
>>> rng = np.random.default_rng(1)
>>> factors = rng.standard_normal((250, 2))
>>> lam = np.array([[1.0, 0.0], [0.5, 1.0], [0.7, -0.3], [0.2, 0.6]])
>>> y = factors @ lam.T + 0.4 * rng.standard_normal((250, 4))
>>> res = FactorSV(y, n_factors=2).fit(n_draws=200, n_burn=50, seed=0)
>>> res.loadings[0], res.loadings[1, 1]
(array([1., 0.]), np.float64(1.0))
>>> bool(np.max(np.abs(res.loadings - lam)) < 0.15)
True