EUNITE.Reg: EUNITE Competition – Regressors for Load Forecasting

In tspredit: Time Series Prediction with Integrated Tuning

EUNITE Competition – Regressors for Load Forecasting

Description

Daily holiday and weekday indicators used as regressors in the EUNITE load forecasting competition. Data Type: Categorical indicators. Category: Benchmark. Observations: 730 (1997–1998). This dataset provides binary holiday flags and weekday identifiers to support the prediction of daily maximum electrical loads. It complements the datasets EUNITE.Loads and EUNITE.Temp. A test set with corresponding regressors for January 1999 is available.

Usage

data(EUNITE.Reg)

Format

A data frame with 730 rows and 3 columns:

Holiday

Binary indicator (1 = holiday, 0 = regular day).

Weekday

Integer encoding (1 = Sunday, ..., 7 = Saturday).

split

Split into train and test

Details

Regressors complement the load profiles by providing daily-level covariates (e.g., holidays and weekdays), which are known to improve forecast accuracy when used with temperature.

Source

EUNITE Competition 2001 dataset (original competition website currently unavailable).

References

Chen, B.-J., Chang, M.-W., & Lin, C.-J. (2004). Load forecasting using support vector machines: a study on EUNITE competition 2001. IEEE Transactions on Power Systems, 19(4), 1821-1830.

Examples

# Load EUNITE regressors
data(EUNITE.Reg)
# EUNITE.Reg <- loadfulldata(EUNITE.Reg)

# Peek at the first rows
head(EUNITE.Reg)

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