Local Influence Diagnostics of Replicated Data with Measurement Errors

Abstract

Replicated data with measurement errors frequently exist in various scientific fields. In this work, we propose a replicated measurement error model for such data under scale mixtures of normal distributions. We consider local influence diagnostics to detect and classify outliers in the data through different perturbation schemes. A simulation study and an application confirm the effectiveness and robustness of the diagnostic method.