DOAJ Open Access 2022

A Novel Correction for the Adjusted Box-Pierce Test

Sidy Danioko Jianwei Zheng Kyle Anderson Alexander Barrett Cyril S. Rakovski

Abstrak

The classical Box-Pierce and Ljung-Box tests for auto-correlation of residuals possess severe deviations from nominal type I error rates. Previous studies have attempted to address this issue by either revising existing tests or designing new techniques. The Adjusted Box-Pierce achieves the best results with respect to attaining type I error rates closer to nominal values. This research paper proposes a further correction to the adjusted Box-Pierce test that possesses near perfect type I error rates. The approach is based on an inflation of the rejection region for all sample sizes and lags calculated via a linear model applied to simulated data that encompasses a large range of data scenarios. Our results show that the new approach possesses the best type I error rates of all goodness-of-fit time series statistics.

Topik & Kata Kunci

Applied mathematics. Quantitative methods Probabilities. Mathematical statistics

Penulis (5)

Sidy Danioko

Jianwei Zheng

Kyle Anderson

Alexander Barrett

Cyril S. Rakovski

Format Sitasi

APA MLA BibTeX

Danioko, S., Zheng, J., Anderson, K., Barrett, A., Rakovski, C.S. (2022). A Novel Correction for the Adjusted Box-Pierce Test. https://doi.org/10.3389/fams.2022.873746

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Informasi Jurnal

Tahun Terbit: 2022
Sumber Database: DOAJ
DOI: 10.3389/fams.2022.873746
Akses: Open Access ✓