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- W2741652912 abstract "Outlier detection for time series data is a fundamental issue in time series analysis. In this work we develop statistical methods in order to detect outliers in time series of counts. More specifically we are interesting on detection of an Innovation Outlier (IO). Models for time series count data were originally proposed by Zeger (Biometrika 75(4):621–629, 1988) [28] and have subsequently generalized into GARMA family. The Maximum Likelihood Estimators of the parameters are discussed and the procedure of detecting an outlier is described. Finally, the proposed method is applied to a real data set." @default.
- W2741652912 created "2017-08-08" @default.
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- W2741652912 date "2017-01-01" @default.
- W2741652912 modified "2023-09-26" @default.
- W2741652912 title "Detection of Outlier in Time Series Count Data" @default.
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- W2741652912 doi "https://doi.org/10.1007/978-3-319-55789-2_15" @default.
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