A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples

@article{Liu2013AHT,
  title={A hypothesis test using bias-adjusted AR estimators for classifying time series in small samples},
  author={Shen Liu and Elizabeth Ann Maharaj},
  journal={Computational Statistics & Data Analysis},
  year={2013},
  volume={60},
  pages={32-49}
}
A new test of hypothesis for classifying stationary time series based on the bias-adjusted estimators of the fitted autoregressive model is proposed. It is shown theoretically that the proposed test has desirable properties. Simulation results show that when time series are short, the size and power estimates of the proposed test are reasonably good, and thus this test is reliable in discriminating between short-length time series. As the length of the time series increases, the performance of… CONTINUE READING
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