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Asian Journal of Mathematics & Statistics
  Year: 2008 | Volume: 1 | Issue: 1 | Page No.: 24-33
DOI: 10.3923/ajms.2008.24.33
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Accommodation of Outliers in Time Series Data: An Alternative Method

Shittu O. Ismail

Considerable attention has been devoted to identification and detection of outliers in discrete univariate samples in time and frequency domains, with less attention paid on what to do with detected outliers. Available techniques for treatment of detected outliers were found to be subjective and deficient. An algorithm is proposed for accommodation of aberrant observations in the frequency domain. A new filtering method of accommodating outliers is also suggested and the performance of various accommodation techniques was determined in respect of the fixed and dynamic models. Five real and analyzed data of sizes (T = 48, 70, 100, 146 and 150) were used in the study. Reductions of between 3.3 and 4.5% in the standard error for both fixed and dynamic models were observed respectively after suspected outliers were accommodated by the filtering method. There was improvement in the precision of the estimates of parameters at (p<0.05) level of significance for both real and simulated data. This work has established that the filtering method of accommodation of outliers is a better and more efficient technique than all existing methods especially when the data are large.
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  •    Estimation of P (Y<X) in the Rayleigh Distribution in the Presence of k Outliers
How to cite this article:

Shittu O. Ismail , 2008. Accommodation of Outliers in Time Series Data: An Alternative Method. Asian Journal of Mathematics & Statistics, 1: 24-33.

DOI: 10.3923/ajms.2008.24.33






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