As a multi-resolution analysis, wavelet transformation tool has been used to detect contingent outliers in time series data with no need to specify a model for the data. The objective of this article is to design an orthonormal wavelet system that optimizes the wavelet-based outlier detection procedure. In addition, we show that regardless of the selected base functions, the existing wavelet-based methods extract two adjacent suspicious observations so that probably one of them is an outlier. Therefore, we modify the wavelet-based outlier detection scheme by introducing a transformation matrix consisting of our designed wavelet filters that can be used to detect outlying observations without the above-mentioned ambiguity. In a numerical example, a sample observation vector is analyzed using our scheme. At the same time, a robust statistical approach- modified z-score method- has been used to evaluate the capability of our desired wavelet-based procedure. The results were completely reliable and comparable.
Moradi,A and Asiaei Mojarad,S . (2019). A modified wavelet-based method for detection of outliers in time series. Earth Observation and Geomatics Engineering, 3(1), 77-83. doi: 10.22059/eoge.2019.285487.1054
MLA
Moradi,A , and Asiaei Mojarad,S . "A modified wavelet-based method for detection of outliers in time series", Earth Observation and Geomatics Engineering, 3, 1, 2019, 77-83. doi: 10.22059/eoge.2019.285487.1054
HARVARD
Moradi A, Asiaei Mojarad S. (2019). 'A modified wavelet-based method for detection of outliers in time series', Earth Observation and Geomatics Engineering, 3(1), pp. 77-83. doi: 10.22059/eoge.2019.285487.1054
CHICAGO
A Moradi and S Asiaei Mojarad, "A modified wavelet-based method for detection of outliers in time series," Earth Observation and Geomatics Engineering, 3 1 (2019): 77-83, doi: 10.22059/eoge.2019.285487.1054
VANCOUVER
Moradi A, Asiaei Mojarad S. A modified wavelet-based method for detection of outliers in time series. Earth Observ. Geomat. Eng.. 2019;3(1):77-83. doi: 10.22059/eoge.2019.285487.1054