On consistency for time series model selection

被引：0

作者：

William Kengne

机构：

[1] THEMA,

[2] CY Cergy Paris Université,undefined

来源：

Statistical Inference for Stochastic Processes | 2023年 / 26卷

关键词：

Model selection; Strong consistency; Weak consistency; Non consistency; Minimum contrast estimation; Causal processes; Multivariate count time series; Penalized contrast; 62M10; 62F07; 62F12;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

We consider the model selection problem for a large class of time series models, including, multivariate count processes, causal processes with exogenous covariates. A procedure based on a general penalized contrast is proposed. Some asymptotic results for weak and strong consistency are established. The non consistency issue is addressed, and a class of penalty term, that does not ensure consistency is provided. Examples of continuous valued and multivariate count autoregressive time series are considered.

引用

页码：437 / 458

页数：21

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