非负自回归模型的估计函数方法

IF 1.4 3区数学 Q2 STATISTICS & PROBABILITY

Statistica Neerlandica Pub Date : 2023-03-31 DOI:10.1111/stan.12294

E. Hari, Prasad N. Balakrishna, E. H. Prasad

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引用次数: 0

摘要

由自回归(AR)模型产生的非负随机变量的平稳序列可用于描述计数过程中事件之间的间隔到达时间。尽管文献中有几个这样的模型，但没有统一的方法来估计它们的参数。本文提出了一类组合估计函数方法来估计具有伽马边际的AR模型的模型参数。将该方法与其他估计方法进行了比较，并通过仿真和数据分析加以说明。

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Estimating function method for nonnegative autoregressive models

A stationary sequence of nonnegative random variables generated by autoregressive (AR) models may be used to describe the inter‐arrival times between events in counting processes. Even though, several such models are available in the literature, there is no unified approach to estimate their parameters. In this paper, we propose a class of combined estimating function method to estimate the model parameters of AR models with gamma marginals. The proposed method is compared with other estimation procedures and are illustrated by simulation and data analysis.

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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.