Quickstart¶
Robust covariance under contamination¶
import numpy as np
import robustcov as rc
rng = np.random.default_rng(0)
X = rng.normal(size=(500, 5))
X[:40] += 8.0
est = rc.FastMCD(quality="balanced", random_state=0).fit(X)
print(est.location_)
print(est.radial_kurtosis_)
rc.plot_robust_distance_panel(est, output_path="distance_panel.png", show=False)
Small-sample heavy-tail scatter¶
est = rc.RegularizedCauchy(alpha=0.10).fit(X)
report = rc.diagnostic_report(est)
print(report.summary())
Automatic estimator selection¶
auto = rc.AutoRobustScatter(selection="diagnostic").fit(X)
print(auto.summary())
cov = auto.covariance_