# skfolio.moments.EmpiricalMu ### *class* skfolio.moments.EmpiricalMu(window_size=None) Empirical Expected Returns (Mu) estimator. Estimates the expected returns with the historical mean. * **Parameters:** **window_size** *int, optional* : Window size. The model is fitted on the last `window_size` observations. The default (`None`) is to use all the data. * **Attributes:** **mu_** *ndarray of shape (n_assets,)* : Estimated expected returns of the assets. **n_features_in_** *int* : Number of assets seen during `fit`. **feature_names_in_** *ndarray of shape (`n_features_in_`,)* : Names of assets seen during `fit`. Defined only when `X` has assets names that are all strings. ### Methods | [`fit`](#skfolio.moments.EmpiricalMu.fit)(X[, y]) | Fit the Mu Empirical estimator model. | |-------------------------------------------------------------------------|-----------------------------------------| | [`get_metadata_routing`](#skfolio.moments.EmpiricalMu.get_metadata_routing)() | Get metadata routing of this object. | | [`get_params`](#skfolio.moments.EmpiricalMu.get_params)([deep]) | Get parameters for this estimator. | | [`set_params`](#skfolio.moments.EmpiricalMu.set_params)(\*\*params) | Set the parameters of this estimator. | #### fit(X, y=None) Fit the Mu Empirical estimator model. * **Parameters:** **X** *array-like of shape (n_observations, n_assets)* : Price returns of the assets. **y** *Ignored* : Not used, present for API consistency by convention. * **Returns:** **self** *EmpiricalMu* : Fitted estimator. #### get_metadata_routing() Get metadata routing of this object. Please check [User Guide](https://skfolio.org/user_guide/metadata_routing.html.md#metadata-routing) on how the routing mechanism works. * **Returns:** **routing** *MetadataRequest* : A `MetadataRequest` encapsulating routing information. #### get_params(deep=True) Get parameters for this estimator. * **Parameters:** **deep** *bool, default=True* : If True, will return the parameters for this estimator and contained subobjects that are estimators. * **Returns:** **params** *dict* : Parameter names mapped to their values. #### set_params(\*\*params) Set the parameters of this estimator. The method works on simple estimators as well as on nested objects (such as `Pipeline`). The latter have parameters of the form `__` so that it’s possible to update each component of a nested object. * **Parameters:** **\*\*params** *dict* : Estimator parameters. * **Returns:** **self** *estimator instance* : Estimator instance.