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.

翻译：我们考虑了一大批时间序列模型的模式选择问题,其中包括多变量计数过程、与外源共差的因果过程,提出了以普遍受罚对比为基础的程序,确立了一些薄弱和强烈一致性的无症状结果,解决了不一致问题,并提供了一个不确保一致性的处罚术语类别,考虑了持续估价和多变量计数自动递减时间序列的例子。