plspm.bootstrap module

class plspm.bootstrap.Bootstrap(config: plspm.config.Config, data: pandas.core.frame.DataFrame, inner_model: plspm.inner_model.InnerModel, outer_model: plspm.outer_model.OuterModel, calculator: plspm.weights.WeightsCalculatorFactory, iterations: int)

Bases: object

Performs bootstrap validation to determine the statistical significance of the model.

Setting bootstrap=True when constructing Plspm will perform bootstrap validation. Calling bootstrap() on Plspm will return an instance of this class, from which the bootstrapping results can be retrieved by calling the methods listed below.

__init__(config: plspm.config.Config, data: pandas.core.frame.DataFrame, inner_model: plspm.inner_model.InnerModel, outer_model: plspm.outer_model.OuterModel, calculator: plspm.weights.WeightsCalculatorFactory, iterations: int)

Initialize self. See help(type(self)) for accurate signature.

loading() → pandas.core.frame.DataFrame

Loadings of manifest variables calculated from bootstrap validation.

paths() → pandas.core.frame.DataFrame

Direct effects for paths calculated from bootstrap validation.

r_squared() → pandas.core.frame.DataFrame

R squared for latent variables calculated from bootstrap validation.

total_effects() → pandas.core.frame.DataFrame

Total effects for paths calculated from bootstrap validation.

weights() → pandas.core.frame.DataFrame

Outer weights calculated from bootstrap validation.