弱FARIMA模型的快速标定

IF 0.6 4区数学 Q4 STATISTICS & PROBABILITY Esaim-Probability and Statistics Pub Date : 2022-06-20 DOI:10.1051/ps/2022021

S. B. Hariz, A. Brouste, Youssef Esstafa, M. Soltane

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引用次数: 1

摘要

本文研究了弱分数自回归积分移动平均(FARIMA)模型的Le Cam一步估计的渐近性质。对于这些模型，噪声是不相关的，但既不是独立的，也不是鞅差误差。在一些正则性假设下，我们证明了一步估计量与最小二乘估计量具有相同的渐近方差，并且是强一致的渐近正态的。通过仿真表明，与最小二乘估计相比，所提出的估计减少了计算时间。提出了一种为时间序列提供远程计算指标的应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Fast calibration of weak FARIMA models

In this paper, we investigate the asymptotic properties of Le Cam's one-step estimator for weak Fractionally AutoRegressive Integrated Moving-Average (FARIMA) models. For these models, noises are uncorrelated but neither necessarily independent nor martingale differences errors. We show under some regularity assumptions that the one-step estimator is strongly consistent and asymptotically normal with the same asymptotic variance as the least squares estimator. We show through simulations that the proposed estimator reduces computational time compared with the least squares estimator. An application for providing remotely computed indicators for time series is proposed.

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来源期刊

Esaim-Probability and Statistics STATISTICS & PROBABILITY-

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The journal publishes original research and survey papers in the area of Probability and Statistics. It covers theoretical and practical aspects, in any field of these domains. Of particular interest are methodological developments with application in other scientific areas, for example Biology and Genetics, Information Theory, Finance, Bioinformatics, Random structures and Random graphs, Econometrics, Physics. Long papers are very welcome. Indeed, we intend to develop the journal in the direction of applications and to open it to various fields where random mathematical modelling is important. In particular we will call (survey) papers in these areas, in order to make the random community aware of important problems of both theoretical and practical interest. We all know that many recent fascinating developments in Probability and Statistics are coming from "the outside" and we think that ESAIM: P&S should be a good entry point for such exchanges. Of course this does not mean that the journal will be only devoted to practical aspects.