In this paper, we propose a new robust non-parametric functional analysis of variance method (RoFANOVA) that reduces the weights of outlying curves on the functional analysis of variance. It is implemented through a permutation test based on a test statistic obtained via a functional M-estimator. The performance of the RoFANOVA is demonstrated through an extensive Monte Carlo simulation study, where it is compared with some alternatives already presented in the literature, and a motivating real-case study related to the analysis of spatter ejections in an additive manufacturing process. The RoFANOVA method is implemented in the R package rofanova, available online on CRAN.

Robust functional ANOVA with application to additive manufacturing

Bianca Maria Colosimo;Marco Luigi Grasso;Alessandra Menafoglio;Simone Vantini
2023-01-01

Abstract

In this paper, we propose a new robust non-parametric functional analysis of variance method (RoFANOVA) that reduces the weights of outlying curves on the functional analysis of variance. It is implemented through a permutation test based on a test statistic obtained via a functional M-estimator. The performance of the RoFANOVA is demonstrated through an extensive Monte Carlo simulation study, where it is compared with some alternatives already presented in the literature, and a motivating real-case study related to the analysis of spatter ejections in an additive manufacturing process. The RoFANOVA method is implemented in the R package rofanova, available online on CRAN.
2023
additive manufacturing
functional analysis of variance
functional data analysis
functional M-estimators
spatters
statistical robustness
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1258482
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