# AUTOGENERATED BY NBDEV! DO NOT EDIT!

__all__ = ["index", "modules", "custom_doc_links", "git_url"]

index = {"AutoARIMAProphet": "adapters.prophet.ipynb",
         "OptimResult": "arima.ipynb",
         "partrans": "arima.ipynb",
         "arima_gradtrans": "arima.ipynb",
         "arima_undopars": "arima.ipynb",
         "tsconv": "arima.ipynb",
         "inclu2": "arima.ipynb",
         "invpartrans": "arima.ipynb",
         "ARIMA_invtrans": "arima.ipynb",
         "getQ0": "arima.ipynb",
         "arima_transpar": "arima.ipynb",
         "arima_css": "arima.ipynb",
         "make_arima": "arima.ipynb",
         "arima_like": "arima.ipynb",
         "diff1d": "arima.ipynb",
         "diff2d": "arima.ipynb",
         "diff": "arima.ipynb",
         "arima": "arima.ipynb",
         "kalman_forecast": "arima.ipynb",
         "checkarima": "arima.ipynb",
         "predict_arima": "arima.ipynb",
         "convert_coef_name": "arima.ipynb",
         "change_drift_name": "arima.ipynb",
         "myarima": "arima.ipynb",
         "search_arima": "arima.ipynb",
         "Arima": "arima.ipynb",
         "arima_string": "arima.ipynb",
         "is_constant": "arima.ipynb",
         "forecast_arima": "arima.ipynb",
         "fitted_arima": "arima.ipynb",
         "mstl": "arima.ipynb",
         "seas_heuristic": "arima.ipynb",
         "nsdiffs": "arima.ipynb",
         "ndiffs": "arima.ipynb",
         "newmodel": "arima.ipynb",
         "auto_arima_f": "arima.ipynb",
         "print_statsforecast_ARIMA": "arima.ipynb",
         "ARIMASummary": "arima.ipynb",
         "AutoARIMA": "arima.ipynb",
         "logger": "core.ipynb",
         "GroupedArray": "core.ipynb",
         "StatsForecast": "core.ipynb",
         "NONE": "ets.ipynb",
         "ADD": "ets.ipynb",
         "MULT": "ets.ipynb",
         "DAMPED": "ets.ipynb",
         "TOL": "ets.ipynb",
         "HUGEN": "ets.ipynb",
         "NA": "ets.ipynb",
         "smalno": "ets.ipynb",
         "NOGIL": "ets.ipynb",
         "CACHE": "ets.ipynb",
         "etscalc": "ets.ipynb",
         "forecast": "ets.ipynb",
         "update": "ets.ipynb",
         "etssimulate": "ets.ipynb",
         "etsforecast": "ets.ipynb",
         "initparam": "ets.ipynb",
         "admissible": "ets.ipynb",
         "check_param": "ets.ipynb",
         "sinpi": "ets.ipynb",
         "cospi": "ets.ipynb",
         "fourier": "ets.ipynb",
         "initstate": "ets.ipynb",
         "switch": "ets.ipynb",
         "pegelsresid_C": "ets.ipynb",
         "restrict_to_bounds": "ets.ipynb",
         "nelder_mead": "ets.ipynb",
         "results": "ets.ipynb",
         "ets_target_fn": "ets.ipynb",
         "optimize_ets_target_fn": "ets.ipynb",
         "etsmodel": "ets.ipynb",
         "ets_f": "ets.ipynb",
         "pegelsfcast_C": "ets.ipynb",
         "forecast_ets": "ets.ipynb",
         "ses": "models.ipynb",
         "ses_optimized": "models.ipynb",
         "adida": "models.ipynb",
         "historic_average": "models.ipynb",
         "croston_classic": "models.ipynb",
         "croston_sba": "models.ipynb",
         "croston_optimized": "models.ipynb",
         "seasonal_window_average": "models.ipynb",
         "imapa": "models.ipynb",
         "naive": "models.ipynb",
         "seasonal_naive": "models.ipynb",
         "random_walk_with_drift": "models.ipynb",
         "window_average": "models.ipynb",
         "seasonal_exponential_smoothing": "models.ipynb",
         "seasonal_ses_optimized": "models.ipynb",
         "tsb": "models.ipynb",
         "auto_arima": "models.ipynb",
         "ets": "models.ipynb",
         "generate_series": "utils.ipynb",
         "AirPassengers": "utils.ipynb"}

modules = ["adapters/prophet.py",
           "arima.py",
           "core.py",
           "ets.py",
           "models.py",
           "utils.py"]

doc_url = "https://Nixtla.github.io/statsforecast/"

git_url = "https://github.com/Nixtla/statsforecast/tree/main/"

def custom_doc_links(name): return None
