rofanova-package {rofanova}

Robust Functional Analysis of Variance

Description

Implements the robust functional analysis of variance (RoFANOVA), described in Centofanti et al. (2021) <arXiv:2112.10643>. It allows testing mean differences among groups of functional data by being robust against the presence of outliers.

Details

Package:	rofanova
Type:	Package
Version:	1.0.0
Date:	2022-01-21
License:	GPL-3

Author(s)

Fabio Centofanti, Bianca Maria Colosimo, Marco Luigi Grasso, Antonio Lepore, Alessandra Menafoglio, Biagio Palumbo, Simone Vantini

References

Centofanti, F., Colosimo, B.M., Grasso, M.L., Menafoglio, A., Palumbo, B., Vantini, S. (2021). Robust Functional ANOVA with Application to Additive Manufacturing. arXiv preprint arXiv:2112.10643.

See Also

rofanova fusem funmad

Examples

library(rofanova)
data_out<-simulate_data(scenario="one-way")
label_1=data_out$label_1
X_fdata<-data_out$X_fdata
B=10
cores=1
per_list_median<-rofanova(X_fdata,label_1,B = B,family="median",cores=cores)
pvalue_median_vec<-per_list_median$pval_vec
per_list_huber<-rofanova(X_fdata,label_1,B = B,family="huber",cores=cores)
pvalue_huber_vec<-per_list_huber$pval_vec
per_list_bisquare<-rofanova(X_fdata,label_1,B = B,family="bisquare",cores=cores)
pvalue_bisquare_vec<-per_list_bisquare$pval_vec
per_list_hampel<-rofanova(X_fdata,label_1,B = B,family="hampel",cores=cores)
pvalue_hampel_vec<-per_list_hampel$pval_vec
per_list_optimal<-rofanova(X_fdata,label_1,B = B,family="optimal",cores=cores)
pvalue_optimal<-per_list_optimal$pval