get_estimator
- pyapprox.multifidelity.get_estimator(estimator_types, stat, costs, max_nmodels=None, **est_kwargs)[source]
- Parameters:
- estimator_typeslist [str] or str
If str (or len(estimators_types==1), then return the estimator named estimator_type (or estimator_types[0])
- stat_typestr
The type of statistics to compute
- costsnp.ndarray (nmodels)
The computational cost of evaluating each model
- stat_argslist or tuple
The arguments that are needed to compute the statistic
- max_nmodelsinteger
If None, compute the estimator using all the models. If not None, find the model subset that uses at most max_nmodels that minimizes the estimator covariance.
- est_kwargsdict
Keyword arguments that will be passed when creating each estimator.