Index

A

AR_quantile_neural_network (class in timeseries_forecast.AR_NN_models)

auto_arch() (timeseries_forecast.parametric.ts_model method) autogluon (class in core.AutoML)

B

base_neural_network (class in core.neural_network_base) beta_pvalues (core.LinearRegression.LinearModel attribute)

betas (core.LinearRegression.LinearModel attribute) betas_se (core.LinearRegression.LinearModel attribute)

C

C (timeseries_forecast.GP_model.PhysicsKernel_CrackGrowth property) check_for_duplicates() (core.LinearRegression.PiecewisePolynomial method) core module core.AutoML module core.knn_models module core.LinearRegression module core.neural_network_base module

core.optimization module core.sensitivity_analysis module core.statistical_tests module core.uncertainty_propagation module core.util module create_images() (core.optimization.GeneticAlgorithm method)

D

default_params (statespace_models.estimators.HiddenVarModel attribute) determine_variable_sensitivity() (core.AutoML.autogluon method)

distribution_difference_hotelling_test() (in module core.statistical_tests) distribution_difference_MC_test() (in module core.statistical_tests)

E

Exponential (class in core.LinearRegression)

F

f() (statespace_models.estimators.HiddenVarModel method) fit() (core.LinearRegression.LinearModel method)

fit_knots() (core.LinearRegression.PiecewisePolynomial method) forward() (timeseries_forecast.GP_model.PhysicsKernel_CrackGrowth method)

G

genetic_algorithm() (core.optimization.GeneticAlgorithm method) GeneticAlgorithm (class in core.optimization) get_estimate() (core.neural_network_base.base_neural_network method) (statespace_models.estimators.kalman method), [1] (statespace_models.estimators.particle_filter method) (timeseries_forecast.GP_model.GPModel method)

get_optimal_n_cluster() (in module core.statistical_tests) GPModel (class in timeseries_forecast.GP_model)

H

HiddenVarModel (class in statespace_models.estimators)

K

kalman (class in statespace_models.estimators)

L

LinearModel (class in core.LinearRegression) load_model() (core.neural_network_base.base_neural_network method) (timeseries_forecast.AR_NN_models.AR_quantile_neural_network method)

load_models() (core.AutoML.autogluon method)

M

m (timeseries_forecast.GP_model.PhysicsKernel_CrackGrowth property) module core core.AutoML core.knn_models core.LinearRegression core.neural_network_base core.optimization core.sensitivity_analysis core.statistical_tests core.uncertainty_propagation core.util statespace_models statespace_models.estimators timeseries_forecast timeseries_forecast.AR_NN_models timeseries_forecast.GP_model timeseries_forecast.parametric

mse (core.LinearRegression.LinearModel attribute)

O

obs_func() (statespace_models.estimators.kalman method)

OutlierKNNDetector (class in core.knn_models)

P

particle_filter (class in statespace_models.estimators) pdf_to_cdf() (in module core.util) PhysicsKernel_CrackGrowth (class in timeseries_forecast.GP_model) PiecewisePolynomial (class in core.LinearRegression) plot() (core.neural_network_base.base_neural_network method) (timeseries_forecast.GP_model.GPModel method) (timeseries_forecast.parametric.ts_model method)

Polynomial (class in core.LinearRegression) predict() (core.AutoML.autogluon method) (core.knn_models.QuantileKNNRegressor method) (core.LinearRegression.LinearModel method) print_parameters() (timeseries_forecast.GP_model.GPModel method) PX() (statespace_models.estimators.HiddenVarModel method) PX0() (statespace_models.estimators.HiddenVarModel method) PY() (statespace_models.estimators.HiddenVarModel method)

Q

QuantileKNNRegressor (class in core.knn_models)

R

remove_outliers() (core.knn_models.OutlierKNNDetector method)

S

save_model() (core.neural_network_base.base_neural_network method) shapely_sensitivity() (in module core.sensitivity_analysis) state_func() (statespace_models.estimators.kalman method)

statespace_models module statespace_models.estimators module

T

timeseries_forecast module timeseries_forecast.AR_NN_models module timeseries_forecast.GP_model module

timeseries_forecast.parametric module train() (core.AutoML.autogluon method) (core.neural_network_base.base_neural_network method) (timeseries_forecast.GP_model.GPModel method) train_test_split() (core.neural_network_base.base_neural_network method) ts_model (class in timeseries_forecast.parametric)

U

uncertainty_propagation() (in module core.uncertainty_propagation)

update_training_data() (timeseries_forecast.GP_model.GPModel method)