2022/10/10 by Alex Rodrigo dos Santos Sousa, Sousa, Alex Rodrigo dos Santos
Chemistry · Mathematics · #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Methodology (stat.ME) #Spectroscopy and Chemometric Analyses
paper · pdf · doi:10.48550/arxiv.2210.04966
openalex publication_date 2022/10/10 · openalex created_date 2022/10/14 · openalex updated_date 2026/07/28
The present work describes simulation studies to compare the performances of bayesian wavelet shrinkage methods in estimating component curves from aggregated functional data. To do so, five methods were considered: the bayesian shrinkage rule under logistic prior by Sousa (2020), bayesian shrinkage rule under beta prior by Sousa et al. (2020), Large Posterior Mode method by Cutillo et al. (2008), Amplitude-scale invariant Bayes Estimator by Figueiredo and Nowak (2001) and Bayesian Adaptive Multiresolution Smoother by Vidakovic and Ruggeri (2001). Further, the so called Donoho-Johnstone test functions, Logit and SpaHet functions were considered as component functions. It was observed that the signal to noise ratio of the data had impact on the performances of the methods.