USING INFLUENCE FUNCTION MATRIX AS OUTLIER DETECTING TOOL BASED ON POOLED SERIAL CORRELATION COEFFICIENTS

S.R.T. Moeng, P.M. Kgosi and D.K. Shangodoyin
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D.K. Shangodoyin: University of Botswana

Analele Stiintifice ale Universitatii "Alexandru Ioan Cuza" din Iasi - Stiinte Economice (1954-2015), 2009, vol. 56, 576-585

Abstract: In this paper, we incorporated autocorrelation function (ACF), partial autocorrelation function (PACF) and inverse auto-correlation function (IACF) into the influence function as a graphical tool for detecting outliers. Depending on the number of positive and negative values of the influence func-tion based on critical values obtained for different lags an observation is identify as outlier. Both the simulated data and Botswana meat sales data confirms the efficacy of using the pooled correlation co-efficients in influence function matrix as outlier detection device.

Keywords: Outliers; Critical values; ACF; PACF; IACF and influence function (search for similar items in EconPapers)
Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:aic:journl:y:2009:v:56:p:576-585

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