trend: Specifying the transformation for dealing with trended series

In utsf: Univariate Time Series Forecasting

Specifying the transformation for dealing with trended series

Description

This function is used to specify the preprocessing associated with the trend of a time series.

Usage

trend(type = "additive", n = -1, transform_features = FALSE)

Arguments

type	A character indicating the type of preprocessing applied to the time series. Possible values are: "none", "additive", "multiplicative" and "differences".
n	An integer specifying the order of first differences to be applied. If the default (-1) is used, the order of first differences needed by the time series will be estimated by the forecast::ndiffs() function. This parameter is only meant when the type parameter is "differences".
transform_features	A logical value indicating whether the training features are also transformed with the additive or multiplicative transformation.

Value

A list with the selected options

Examples

trend("none")            # no preprocessing
trend("additive")        # additive preprocessing
trend("differences", 1)  # order 1 first differences
trend("differences", -1) # order of first differences automatically estimated

utsf documentation built on June 8, 2025, 10:44 a.m.