arviz.r2_score#

arviz.r2_score(y_true, y_pred)[source]#

R² for Bayesian regression models. Only valid for linear models.

Parameters:

y_true: array-like of shape = (n_outputs,): Ground truth (correct) target values.
y_pred: array-like of shape = (n_posterior_samples, n_outputs): Estimated target values.

Returns:

Pandas Series with the following indices:
r2: Bayesian R²
r2_std: standard deviation of the Bayesian R².

See also

plot_lm: Posterior predictive and mean plots for regression-like data.

Examples

Calculate R² for Bayesian regression models :

In [1]: import arviz as az
   ...: data = az.load_arviz_data('regression1d')
   ...: y_true = data.observed_data["y"].values
   ...: y_pred = data.posterior_predictive.stack(sample=("chain", "draw"))["y"].values.T
   ...: az.r2_score(y_true, y_pred)
   ...: 
Out[1]: 
r2        0.683197
r2_std    0.036884
dtype: float64