Wavelet-Based Detection of Outliers in Time Series

AbstractThis article considers the problem of detecting outliers in time series data and proposes a general detection method based on wavelets. Unlike other detection procedures found in the literature, our method does not require that a model be specified for the data. Also, use of our method is not restricted to data generated from ARIMA processes. The effectiveness of the proposed method is compared with existing outlier detection procedures. Comparisons based on various models, sample sizes, and parameter values illustrate the effectiveness of the proposed method.