Outliers detect methods for time series data
T. X. Liang, Chunxiang Cao · Journal of Discrete Mathematical Sciences and Cryptography · 2018
The outliers are unavoidable anomalous points. It will affect the accuracy of time series data. A method of outlier detection and correction for time series data based on statistics is designed in this paper, which can effectively detect the position of anomalous points and make correction. The numerical experimental resultson hotel room night data show that the accuracy of the compressed dataset is improved by 3.4% to 4.4% compared with the original dataset.