Model Checking via Parametric Bootstraps in Time Series Analysis
本文利用参数自助法和谱密度函数等工具，提出了时间序列模型检验方法，强调模型的可重复性，可用于检验时间可逆性和长记忆依赖等特性，并以爱尔兰风速数据为例进行说明。
SUMMARY This paper uses parametric bootstraps in conjunction with selected functionals such as the spectral density function to derive methods for model checking in time series analysis. The methods proposed emphasize the reproducibilities of the fitted models. They are widely applicable and easy to implement. In particular, they can be used to check special characteristics of the underlying process such as time reversibility and long memory dependence. The paper also addresses the importance of model-building objectives in model checking. Several examples including a wind speed data set for Ireland are used to illustrate the procedures proposed.