论文标题
时间序列模型选择的一些渐近结果
Some asymptotic results for time series model selection
论文作者
论文摘要
我们考虑了大型时间序列模型的模型选择问题，包括具有外源协变量的多元计数过程，因果过程。提出了基于一般惩罚对比的程序。建立了一些针对弱和强一致性的渐近结果。解决了非一致性问题，并不能确保提供一致性。考虑了连续价值和多元计数自回归时间序列的示例。
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.
