Geodesic
Robust sign test for the unit root hypothesis of autoregression
Teoriâ veroâtnostej i ee primeneniâ, Tome 63 (2018) no. 3, pp. 431-446

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An $\operatorname{AR}(1)$-model is considered with autoregression observations that contain gross errors (contaminations) with unknown arbitrary distribution. The unit root hypothesis for autoregression is tested. A special sign test is proposed as an alternative to the least-square test (the latter test is not applicable in this setting). The sign test is shown to be locally qualitatively robust in terms of the equicontinuity of the power.
Keywords: hypotheses testing, unit root, sign tests, qualitative robustness.
Mots-clés : autoregression, contaminations 
@article{TVP_2018_63_3_a1,
     author = {M. V. Boldin},
     title = {Robust sign test for the unit root hypothesis of autoregression},
     journal = {Teori\^a vero\^atnostej i ee primeneni\^a},
     pages = {431--446},
     publisher = {mathdoc},
     volume = {63},
     number = {3},
     year = {2018},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/TVP_2018_63_3_a1/}
}
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M. V. Boldin. Robust sign test for the unit root hypothesis of autoregression. Teoriâ veroâtnostej i ee primeneniâ, Tome 63 (2018) no. 3, pp. 431-446. http://geodesic.mathdoc.fr/item/TVP_2018_63_3_a1/