التفاصيل البيبلوغرافية
| العنوان: |
Unified inference for an integer-valued AR(1) model. |
| المؤلفون: |
Chen, Longyu1 (AUTHOR), Liu, Xiaohui2 (AUTHOR), Peng, Liang3 (AUTHOR) zfk8010@163.com, Zhu, Fukang1 (AUTHOR) |
| المصدر: |
Communications in Statistics: Theory & Methods. Oct2024, p1-11. 11p. 2 Illustrations. |
| مصطلحات موضوعية: |
LEAST squares, COVID-19 testing, HYPOTHESIS |
| مستخلص: |
Abstract.Conditional least squares estimation is often employed to infer an integer-valued AR(1) model and its convergence rate and asymptotic variance differ for the stable and nearly unstable cases. This article adopts a random weighted bootstrap method to provide a unified interval estimation and hypothesis test regardless of the underlying process being either stable or nearly unstable. A simulation study confirms the good finite sample performance of the proposed inference. We also apply it to test for a unit root test in a COVID-19 dataset. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Business Source Index |