model

sgp.models.model.ANN

Bases: PredictionBase

Artificial Neural Network (ANN) model.

sgp.models.model.MPD

Bases: PredictionBase

Multivariate Distribution (MPD) model.

sgp.models.model.MPD.corr_bootstrap

corr_bootstrap(X: ndarray) -> ndarray

Calculate the correlation matrix.

sgp.models.model.MPD.dist

dist() -> MPDDistributionalResults

Get the distributional results.

sgp.models.model.MPD.fit

fit()

Fit the Johnson distribution to the data.

RETURNS	DESCRIPTION
A tuple containing the distributions, the optimization results, the statistics, and the p-values.

sgp.models.model.MPD.optimize

optimize(df: DataFrame, *, method: Optimizers, **kwargs)

Optimize the z-value for the Johnson distribution.

sgp.models.model.Model

The prediction model

sgp.models.model.Model.__init__

__init__(io: SGPIO)

Initialize the model.

sgp.models.model.SGPIO

Bases: HashableBaseModelIO