ts_windows: Build a lagged-feature table from one or more time series

In SynthesizerPlus: Synthetic Data Generation with Copulas, Evaluation and Multi-Format I/O

Build a lagged-feature table from one or more time series

Description

Converts time series into a data frame suitable for training forecasting models: each row holds the target y (the value horizon steps ahead) and the lags preceding values lag1 (most recent) ... lagp. With a list of series (e.g. from augment_data()), the windows of all series are stacked and a series column identifies their origin; windows never cross series boundaries.

Usage

ts_windows(x, lags, horizon = 1L, target = 1L)

Arguments

x	A ts object, numeric vector/matrix, or a list of them.
lags	Number of lags.
horizon	Forecast horizon (1 = one step ahead).
target	For multivariate series: name or index of the target column.

Details

For multivariate series, lags of every component are created (⁠<name>_lag1⁠, ...) and the target is the column named by target.

Value

A data frame with columns y, the lag columns and (for lists) series.

Examples

w <- ts_windows(ldeaths, lags = 3)
head(w)
fit <- lm(y ~ ., data = w)

SynthesizerPlus documentation built on Oct. 16, 2026, 5:10 p.m.