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
收藏
页码：437 / 458
页数：21
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