TSLM: Fit a linear model with time series components

In fable: Forecasting Models for Tidy Time Series

Fit a linear model with time series components

Description

The model formula will be handled using stats::model.matrix(), and so the the same approach to include interactions in stats::lm() applies when specifying the formula. In addition to stats::lm(), it is possible to include common_xregs in the model formula, such as trend(), season(), and fourier().

Usage

TSLM(formula)

Arguments

formula

Model specification.

Value

A model specification.

Specials

xreg

Exogenous regressors can be included in a TSLM model without explicitly using the xreg() special. Common exogenous regressor specials as specified in common_xregs can also be used. These regressors are handled using stats::model.frame(), and so interactions and other functionality behaves similarly to stats::lm().

xreg(...)

...	Bare expressions for the exogenous regressors (such as log(x))

See Also

stats::lm(), stats::model.matrix() Forecasting: Principles and Practices, Time series regression models (chapter 6)

Examples

as_tsibble(USAccDeaths) %>%
  model(lm = TSLM(log(value) ~ trend() + season()))

library(tsibbledata)
olympic_running %>%
  model(TSLM(Time ~ trend())) %>%
  interpolate(olympic_running)

fable documentation built on March 31, 2023, 8:13 p.m.