Supplement to "Aligning Validation with Deployment in Spatial Prediction: Target-Weighted Cross-Validation"

This repository contains code, data, and supplementary material for the manuscript “Aligning Validation with Deployment in Spatial Prediction: Target-Weighted Cross-Validation” by Brenning and Suesse. It implements a deployment-oriented framework for performance estimation in spatial prediction, including Target-Weighted Cross-Validation (TWCV) and importance-weighted cross-validation (IWCV). The codebase provides modular components for task generation (random CV, spatial CV, buffered LOO, kNNDM), weighting, and risk estimation, along with simulation experiments and a real-world air-quality (NO₂) case study. The accompanying Supplement document (PDF) presents methodological details and results. The Supplement document is provided under CC-BY, and the code under GPL 3.0. Updated code may be available in the corresponding Github repository at https://github.com/alexanderbrenning/TWCVpaper All results are fully reproducible using the provided R scripts. Data sources and licenses are documented in the Supplement document.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-08
DOI
https://doi.org/10.5281/zenodo.20090837
Primary Topic
Spatial and Panel Data Analysis
Type
article
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article

Supplement to "Aligning Validation with Deployment in Spatial Prediction: Target-Weighted Cross-Validation"

Alexander Brenning, Thomas Suesse
Zenodo (CERN European Organization for Nuclear Research)
Spatial and Panel Data Analysis
article

Supplement to "Aligning Validation with Deployment in Spatial Prediction: Target-Weighted Cross-Validation"

Alexander Brenning, Thomas Suesse
article en

Abstract

This repository contains code, data, and supplementary material for the manuscript “Aligning Validation with Deployment in Spatial Prediction: Target-Weighted Cross-Validation” by Brenning and Suesse. It implements a deployment-oriented framework for performance estimation in spatial prediction, including Target-Weighted Cross-Validation (TWCV) and importance-weighted cross-validation (IWCV). The codebase provides modular components for task generation (random CV, spatial CV, buffered LOO, kNNDM), weighting, and risk estimation, along with simulation experiments and a real-world air-quality (NO₂) case study. The accompanying Supplement document (PDF) presents methodological details and results. The Supplement document is provided under CC-BY, and the code under GPL 3.0. Updated code may be available in the corresponding Github repository at https://github.com/alexanderbrenning/TWCVpaper All results are fully reproducible using the provided R scripts. Data sources and licenses are documented in the Supplement document.

Zenodo (CERN European Organization for Nuclear Research)
Friedrich Schiller University Jena (DE)
Openalex Percentile: Top 2%
Spatial and Panel Data Analysis
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