ets_fit_impl: Low-Level Exponential Smoothing function for translating...

In modeltime: The Tidymodels Extension for Time Series Modeling

Low-Level Exponential Smoothing function for translating modeltime to forecast

Description

Low-Level Exponential Smoothing function for translating modeltime to forecast

Usage

ets_fit_impl(
  x,
  y,
  period = "auto",
  error = "auto",
  trend = "auto",
  season = "auto",
  damping = "auto",
  alpha = NULL,
  beta = NULL,
  gamma = NULL,
  ...
)

Arguments

x	A dataframe of xreg (exogenous regressors)
y	A numeric vector of values to fit
period	A seasonal frequency. Uses "auto" by default. A character phrase of "auto" or time-based phrase of "2 weeks" can be used if a date or date-time variable is provided.
error	The form of the error term: "auto", "additive", or "multiplicative". If the error is multiplicative, the data must be non-negative.
trend	The form of the trend term: "auto", "additive", "multiplicative" or "none".
season	The form of the seasonal term: "auto", "additive", "multiplicative" or "none".
damping	Apply damping to a trend: "auto", "damped", or "none".
alpha	Value of alpha. If NULL, it is estimated.
beta	Value of beta. If NULL, it is estimated.
gamma	Value of gamma. If NULL, it is estimated.
...	Additional arguments passed to forecast::ets

modeltime documentation built on Oct. 23, 2024, 1:07 a.m.