一种新的LARCH过程估计方法

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-03-27 DOI:10.1111/jtsa.12689

Jean-Marc Bardet

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引用次数: 1

摘要

本文的目的是为LARCH $(\infty)$过程提供一种新的参数估计，从而也为LARCH $(p)$或GLARCH $(p,q)$过程提供一种新的参数估计。这个估计量是通过最小化导致过程绝对值的最小二乘估计量的对比度得到的。强一致性和渐近正态性表明，收敛发生在速率$\sqrt n$以及短或长记忆的情况下。数值实验证实了理论结果，并表明该估计量明显优于光滑拟极大似然估计量或加权最小二乘估计量。

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A new estimator for LARCH processes

The aim of this article is to provide a new estimator of parameters for LARCH $(\infty)$ processes, and thus also for LARCH $(p)$ or GLARCH $(p, q)$ processes. This estimator results from minimizing a contrast leading to a least squares estimator for the absolute values of the process. Strong consistency and asymptotic normality are shown, and convergence occurs at the rate $\sqrt{n}$ as well in short or long memory cases. Numerical experiments confirm the theoretical results and show that this new estimator significantly outperforms the smoothed quasi-maximum likelihood estimators or weighted least squares estimators commonly used for such processes.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.