Wavelet-based detection of outliers in time series of counts
Isabel Vanessa de Assis Silva, Maria Eduarda Silva · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2016
In this work we consider the problem of analysing count time series contaminated with outliers. To address this problem we propose a wavelet-based approach that allows the identification of the time point of occurrence of an outlier in a time series of counts, by using the empirical distribution of the detail coefficient via resampling methods (parametric bootstrap). Results of a simulation study illustrating the effectiveness of the proposed method and a real dataset application are presented.