Man pages for opoyc/autoforecast
Forecast Development Kit

accuracy_metric	Accuracy metrics
clean_ts	Time Series Cleansing
feature_engineering_ts	Automatic Time Series Feature Engineering
fit_arima	Fit Auto Regressive Integrated Moving Average Model
fit_croston	Fit Croston model
fit_ets	Fit Error Trend Seasonal model
fit_gam	Fit Generalized Additive Model
fit_glm	Fit a Generalized Linear Model
fit_glmnet	Fit a Regularized Generalize Linear Model
fit_ts	Fitting models for time-series data
get_default_hyperpar	Default hyperparameter list by time series model
get_default_optim_conf	Default optimization configuration
get_graph_stat	Generate graphics for time series insights
get_hyperpar_sample	Hyperparameter sample generator
get_insight_data	Get GAM features
get_oc_data	Get Operational Cycle data
get_seas_me	Calculate Marginal Seasonal Effects
get_time_weights	Generate time weights
get_trend_decay	Generate trend discounts
import_data	Importing data from local and shared sources
impute_ts	Time series imputation
lag_features	Autoregressive or lags features
log_update	Logger updater
long_to_wide	Long to wide regressor column
ma_features	Moving Average feature engineering
make_reg_matrix	Generate regression matrix for regression based models
mod_stat_data	Internal modification of statistical data
optim_int	Time series optimization internal function
optim_ts	High order optimization function
plot_ts	Plot time series forecast
prescribe_ts	Data prescription
rdata2obj	RData 2 Object
react_gam_par	Internal GAM parameter
reverse_scope	Reverse scope
seasonal_features	Generate trend and seasonal components for regression based...
split_ts	Automatic Time Series Cross-Validation split
update_parameter	Updating parameters given a grid.
validate_ts	Validate Time Series Data
winsorize_ts	Winsorize imputation