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An Outlier Test For Time Series Based On A Two‐Sided Predictor

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  • W. Schmid

Abstract

. In this paper an outlier test for contaminated autoregressive processes is introduced. The test is based on a comparison of each observation with a predictor using past and future values, a so‐called two‐sided predictor. It is required that an upper bound for the total number of outliers is known. The asymptotic distribution of the test statistic is calculated under the null hypothesis that no outlier is present. The behaviour of the test for finite sample size is investigated by a simulation study. Moreover, the test is compared with several other outlier tests.

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  • W. Schmid, 1996. "An Outlier Test For Time Series Based On A Two‐Sided Predictor," Journal of Time Series Analysis, Wiley Blackwell, vol. 17(5), pages 497-510, September.
    • Handle: RePEc:bla:jtsera:v:17:y:1996:i:5:p:497-510
    DOI: 10.1111/j.1467-9892.1996.tb00290.x
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    Cited by:

    1. R. H. Glendinning, 2000. "Estimating the Inverse Autocorrelation Function from Outlier Contaminated Data," Computational Statistics, Springer, vol. 15(4), pages 541-565, December.

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