2023/08/09 by Fabio Centofanti, Bianca Maria Colosimo, Marco Luigi Grasso +4 · 1 citation
Decision Sciences · Mathematics · #Advanced Statistical Methods and Models #Optimal Experimental Design Methods #Statistical Methods and Inference
paper · pdf · doi:10.1093/jrsssc/qlad074
crossref issued 2023/08/09 · crossref published 2023/08/09 · crossref published-online 2023/08/09 · openalex publication_date 2023/08/09 · crossref created 2023/08/09 · crossref published-print 2023/12/22 · crossref deposited 2023/12/23 · openalex created_date 2025/10/10 · crossref indexed 2026/08/02 · openalex updated_date 2026/08/02
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.