ForeComp: An R Package for Comparing Predictive Accuracy Using Fixed-Smoothing Asymptotics
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arXiv
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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866917322384474112 |
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| author | Shin, Minchul Schor, Nathan |
| author_facet | Shin, Minchul Schor, Nathan |
| contents | We introduce ForeComp, an R package for comparing predictive accuracy using Diebold-Mariano type tests of equal predictive ability with standard and fixed smoothing inference. The package provides a common interface for loss differential based testing and includes Plot Tradeoff, a visual diagnostic for bandwidth sensitivity and the size-power tradeoff. We illustrate the toolkit with Survey of Professional Forecasters applications and Monte Carlo evidence on finite-sample performance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_07458 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | ForeComp: An R Package for Comparing Predictive Accuracy Using Fixed-Smoothing Asymptotics Shin, Minchul Schor, Nathan Econometrics Applications We introduce ForeComp, an R package for comparing predictive accuracy using Diebold-Mariano type tests of equal predictive ability with standard and fixed smoothing inference. The package provides a common interface for loss differential based testing and includes Plot Tradeoff, a visual diagnostic for bandwidth sensitivity and the size-power tradeoff. We illustrate the toolkit with Survey of Professional Forecasters applications and Monte Carlo evidence on finite-sample performance. |
| title | ForeComp: An R Package for Comparing Predictive Accuracy Using Fixed-Smoothing Asymptotics |
| topic | Econometrics Applications |
| url | https://arxiv.org/abs/2603.07458 |