具有空间相关性的非参数分位数估计的渐近性质

IF 1.4 3区数学 Q2 STATISTICS & PROBABILITY

Statistica Neerlandica Pub Date : 2022-11-10 DOI:10.1111/stan.12284

Serge-Hippolyte Arnaud Kanga, O. Hili, S. Dabo‐Niang, Assi N'Guessan

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引用次数: 0

摘要

本文的目的是对局部平稳多元空间过程的条件分位数进行非参数估计。从条件分布函数(CDF)的核分位数估计出发，提出了新的核分位数估计。本文的独创性是基于在估计CDF形式中考虑一些局部空间依赖性的能力。在α $$ \alpha $$‐混合条件下，得到了估计的一致性和渐近正态性。通过数值研究和对实际数据的应用，说明了本文方法的有效性。

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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Asymptotic properties of nonparametric quantile estimation with spatial dependency

The purpose of this work is to nonparametrically estimate the conditional quantile for a locally stationary multivariate spatial process. The new kernel quantile estimate derived from the one of conditional distribution function (CDF). The originality in the paper is based on the ability to take into account some local spatial dependency in estimate CDF form. Consistency and asymptotic normality of the estimates are obtained under α$$ \alpha $$ ‐mixing condition. Numerical study and application to real data are given in order to illustrate the performance of our methodology.

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来源期刊

Statistica Neerlandica 数学-统计学与概率论

CiteScore

2.60

自引率

6.70%

发文量

审稿时长

>12 weeks

期刊介绍： Statistica Neerlandica has been the journal of the Netherlands Society for Statistics and Operations Research since 1946. It covers all areas of statistics, from theoretical to applied, with a special emphasis on mathematical statistics, statistics for the behavioural sciences and biostatistics. This wide scope is reflected by the expertise of the journal’s editors representing these areas. The diverse editorial board is committed to a fast and fair reviewing process, and will judge submissions on quality, correctness, relevance and originality. Statistica Neerlandica encourages transparency and reproducibility, and offers online resources to make data, code, simulation results and other additional materials publicly available.