MinimizeMixedEffectsConverter#

class skfda.representation.conversion.MinimizeMixedEffectsConverter(basis)[source]#

Mixed effects to-basis-converter using scipy.optimize.minimize.

Minimizes the profile loglikelihood of the mixed effects model as proposed by Lindstrom and Bates[1].

Methods

`fit`(X[, y, initial_params, ...])	Fit the model.
`fit_transform`(X[, y])	Fit to data, then transform it.
`set_output`(*[, transform])	Set output container.
`transform`(X)	Transform X to FDataBasis using the fitted converter.

fit(X, y=None, *, initial_params=None, minimization_method=None, has_mean=True)[source]#

Fit the model.

Parameters:

X (FDataIrregular) – irregular data to fit.
y (object) – ignored.
initial_params (Params | ndarray[tuple[int, ...], dtype[floating[Any]]] | None) – initial params of the model.
minimization_method (str | None) – scipy.optimize.minimize method to be used for the minimization of the loglikelihood of the model.
has_mean (bool) – Whether the mean is a fixed parameter to be optimized or estimated with ML estimator from the covariance parameters.

Returns:

self after fit

Return type:

Self

fit_transform(X, y=None, **fit_params)[source]#

Fit to data, then transform it.

Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.

Parameters:

X (array-like of shape (n_samples, n_features)) – Input samples.
y (array-like of shape (n_samples,) or (n_samples, n_outputs), default=None) – Target values (None for unsupervised transformations).
**fit_params (dict) – Additional fit parameters.

Returns:

X_new – Transformed array.

Return type:

ndarray array of shape (n_samples, n_features_new)

set_output(*, transform=None)#

Set output container.

See Introducing the set_output API for an example on how to use the API.

Parameters:

transform ({"default", "pandas", "polars"}, default=None) –

Configure output of transform and fit_transform.

Added in version 1.4: “polars” option was added.

Returns:

self – Estimator instance.

Return type:

estimator instance

transform(X)[source]#

Transform X to FDataBasis using the fitted converter.