Index

_

__post_init__() (sforecast.endogenous_transforms.rolling_transformer method) (sforecast.rolling_transformer method)

__version__ (in module sforecast) _minmax (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

C

ci (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute) ci_percentile() (in module sforecast.sliding_forecast) ci_tdistribution() (in module sforecast.sliding_forecast) cm_params (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

covarlags (class in sforecast) (class in sforecast.sliding_forecast) covars (sforecast.covarlags attribute) (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.covarlags attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

D

dfmemory (sforecast.covarlags attribute) (sforecast.endogenous_transforms.rolling_transformer attribute) (sforecast.rolling_transformer attribute) (sforecast.sliding_forecast.covarlags attribute)

dfXYfit_last (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute) donotscale_cols (sforecast.sliding_forecast.minmaxstd_scaler attribute)

E

exenvars (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

F

fit() (sforecast.covarlags method) (sforecast.endogenous_transforms.rolling_transformer method) (sforecast.rolling_transformer method) (sforecast.sliding_forecast method) (sforecast.sliding_forecast.covarlags method) (sforecast.sliding_forecast.minmaxstd_scaler method) (sforecast.sliding_forecast.sliding_forecast method)

forecast_confidence() (in module sforecast.sliding_forecast)

G

get_dense_emb_nn() (in module sforecast) (in module sforecast.forecast_neural_networks) get_dense_nn() (in module sforecast) (in module sforecast.forecast_neural_networks) get_derived_attribute_names() (sforecast.endogenous_transforms.rolling_transformer method) (sforecast.rolling_transformer method)

get_last_dfrow() (sforecast.covarlags method) (sforecast.sliding_forecast.covarlags method) get_Nclip() (sforecast.endogenous_transforms.rolling_transformer method) (sforecast.rolling_transformer method)

H

history_i (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

history_t (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

I

idx_last_obs (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

M

max_func() (in module sforecast.sliding_forecast) max_vfunc (in module sforecast.sliding_forecast) metrics (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute) min_func() (in module sforecast.sliding_forecast) min_vfunc (in module sforecast.sliding_forecast) minmax (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute) minmaxstd_scaler (class in sforecast.sliding_forecast)

mms_cols (sforecast.sliding_forecast.minmaxstd_scaler attribute) mmscaler (sforecast.sliding_forecast.minmaxstd_scaler attribute) model_type (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute) module sforecast sforecast.endogenous_transforms sforecast.forecast_neural_networks sforecast.sliding_forecast

N

Nhorizon (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute) nlag_covars() (in module sforecast.sliding_forecast) Nlags (sforecast.covarlags attribute) (sforecast.sliding_forecast.covarlags attribute)

Nmemory (sforecast.covarlags attribute) (sforecast.sliding_forecast.covarlags attribute) Nrw (sforecast.endogenous_transforms.rolling_transformer attribute) (sforecast.rolling_transformer attribute)

P

predict() (sforecast.sliding_forecast method) (sforecast.sliding_forecast.sliding_forecast method)

predict_params (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

R

rolling_transformer (class in sforecast) (class in sforecast.endogenous_transforms)

S

scale_params (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute) set_last_y() (sforecast.covarlags method) (sforecast.sliding_forecast.covarlags method) sforecast module sforecast.endogenous_transforms module sforecast.forecast_neural_networks module

sforecast.sliding_forecast module slider() (in module sforecast.sliding_forecast) sliding_forecast (class in sforecast) (class in sforecast.sliding_forecast) ss_cols (sforecast.sliding_forecast.minmaxstd_scaler attribute) sscaler (sforecast.sliding_forecast.minmaxstd_scaler attribute) swin_params (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)

T

tf_params (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute) train_test_predict() (in module sforecast.sliding_forecast) transform() (sforecast.covarlags method) (sforecast.endogenous_transforms.rolling_transformer method) (sforecast.rolling_transformer method) (sforecast.sliding_forecast.covarlags method) (sforecast.sliding_forecast.minmaxstd_scaler method)

V

variable_transform_dict (sforecast.endogenous_transforms.rolling_transformer attribute) (sforecast.rolling_transformer attribute)

Y

y (sforecast.sliding_forecast attribute) (sforecast.sliding_forecast.sliding_forecast attribute)