Yao's test is a statistical method used to evaluate the performance of predictive models, particularly in the context of time series forecasting or comparing different models. The test is named after the statistician Yanqing Yao. In essence, Yao's test is designed to assess the accuracy of forecasts by comparing the predictions made by two or more models. The test involves the following steps: 1. **Fit the Models**: Apply the models to the same dataset and generate predictions.
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