ts_aug_wormhole: Augmentation by Wormhole

In tspredit: Time Series Prediction with Integrated Tuning

Augmentation by Wormhole

Description

Generate augmented windows by selectively replacing lag terms with older lagged values, creating plausible alternative trajectories.

Usage

ts_aug_wormhole()

Details

This combinatorial replacement preserves overall scale while introducing temporal permutations of lag content.

Value

A ts_aug_wormhole object.

References

• Q. Wen et al. (2021). Time Series Data Augmentation for Deep Learning: A Survey. IJCAI Workshop on Time Series.

Examples

# Wormhole augmentation replaces some lags with older values
# Load package and example dataset
library(daltoolbox)
data(tsd)

# Convert to sliding windows and preview
xw <- ts_data(tsd$y, 10)
ts_head(xw)

# Apply wormhole augmentation and inspect augmented windows
augment <- ts_aug_wormhole()
augment <- fit(augment, xw)
xa <- transform(augment, xw)
ts_head(xa)

tspredit documentation built on Feb. 11, 2026, 9:08 a.m.