Detection of outliers in mixed regressive-spatial autoregressive models

Libin Jin, Xiaowen Dai, Anqi Shi and Lei Shi

Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 17, 5179-5192

Abstract: This article studies the outlier detection problem in mixed regressive-spatial autoregressive model. The formulae for testing outliers and their approximate distributions are derived under the mean-shift model and the variance-weight model, respectively. The simulation studies are conducted for examining the power and size of the test, as well as for the detection of outliers when a simulated data contains several outliers. A real data is analyzed to illustrate the proposed method, and modified models based on mean-shift and variance-weight models in which detected outliers are taken into account are suggested to deal with the outliers and confirm theconclusions.

Date: 2016
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DOI: 10.1080/03610926.2014.941493

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