Robust functional ANOVA model with t-process

2018/12/18 by Chen Zhang, Zhang, Chen, Zimu Chen +5
Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #Advanced Statistical Process Monitoring #FOS: Computer and information sciences #Methodology (stat.ME) #Optimal Experimental Design Methods

paper · pdf · doi:10.48550/arxiv.1812.07173

openalex publication_date 2018/12/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Robust estimation approaches are of fundamental importance for statistical modelling. To reduce susceptibility to outliers, we propose a robust estimation procedure with t-process under functional ANOVA model. Besides common mean structure of the studied subjects, their personal characters are also informative, especially for prediction. We develop a prediction method to predict the individual effect. Statistical properties, such as robustness and information consistency, are studied. Numerical studies including simulation and real data examples show that the proposed method performs well.

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