On Symmetrized Pearson's Type Test in Autoregression with Outliers: Robust Testing of Normality

2020/03/17 by Michael Boldin, Boldin, Michael · 1 citation
Economics, Econometrics and Finance · Mathematics · #62G10 (Primary) 62M10 #62G30 #62G35 (Secondary) #Advanced Statistical Methods and Models #FOS: Mathematics #Financial Risk and Volatility Modeling #Statistical Distribution Estimation and Applications #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.2003.07878

openalex publication_date 2020/03/17 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We consider a stationary linear AR(p) model with observations subject to gross errors (outliers). The autoregression parameters are unknown as well as the distribution and moments of innoovations. The distribution of outliers Π is unknown and arbitrary, their intensity is γn^-1/2 with an unknown γ, n is the sample size. The autoregression parameters are estimated by any estimator which is n^1/2-consistent uniformly in γ≤ Γ

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• On the Power of Symmetrized Pearson's Type Test under Local Alternatives in Autoregression with Outliers

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