基于时间和空间增量的二维空间线性抛物线 SPDE 参数估计

IF 0.9 4区数学 Q3 STATISTICS & PROBABILITY

Metrika Pub Date : 2024-05-18 DOI:10.1007/s00184-024-00969-x

Yozo Tonaki, Yusuke Kaino, Masayuki Uchida

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引用次数: 0

摘要

我们以时间和空间的高频数据为基础，讨论了两维空间中由两类 Q-Wiener 过程驱动的线性抛物线二阶随机偏微分方程的参数估计。我们提出了基于时间和空间增量的系数参数最小对比度估计器，并提供了基于近似坐标过程的系数参数自适应估计器。我们还给出了一个例子和所提估计器的仿真结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Parametric estimation for linear parabolic SPDEs in two space dimensions based on temporal and spatial increments

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Parametric estimation for linear parabolic SPDEs in two space dimensions based on temporal and spatial increments

We deal with parameter estimation for linear parabolic second-order stochastic partial differential equations in two space dimensions driven by two types of Q-Wiener processes based on high frequency data with respect to time and space. We propose minimum contrast estimators of the coefficient parameters based on temporal and spatial increments, and provide adaptive estimators of the coefficient parameters based on approximate coordinate processes. We also give an example and simulation results of the proposed estimators.

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来源期刊

Metrika 数学-统计学与概率论

CiteScore

1.50

自引率

14.30%

发文量

审稿时长

6-12 weeks

期刊介绍： Metrika is an international journal for theoretical and applied statistics. Metrika publishes original research papers in the field of mathematical statistics and statistical methods. Great importance is attached to new developments in theoretical statistics, statistical modeling and to actual innovative applicability of the proposed statistical methods and results. Topics of interest include, without being limited to, multivariate analysis, high dimensional statistics and nonparametric statistics; categorical data analysis and latent variable models; reliability, lifetime data analysis and statistics in engineering sciences.