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动态回归模型中的异常值检测与处理
This paper offers an approach to detecting outliers in multiple time series by studying transfer functions with one input where outliers in the input may or may not be passed to the output.
利用动态回归模型进行预测
A Primer on ARIMA Models. A Primer on Regression Models. Rational Distributed Lag Models. Building Dynamic Regression Models: Model Identification. Building Dynamic Regression Models: Model Checking, Reformulation, and Evaluation. Intervention Analysis. Intervention and Outlier Detection and Treatment. Estimation and Forecasting. Dynamic Regression Models in a Vector ARMA Framework. Appendices. References. Index.
This paper offers an approach to detecting outliers in multiple time series by studying transfer functions with one input where outliers in the input may or may not be passed to the output.