Cluster analysis: a further approach based on density estimation
Computational Statistics & Data Analysis
Estimation in generalized linear models for functional data via penalized likelihood
Journal of Multivariate Analysis
Modern Applied Statistics with S
Modern Applied Statistics with S
Functional data analysis for non homogeneous Poisson processes
Proceedings of the 40th Conference on Winter Simulation
Measures of influence for the functional linear model with scalar response
Journal of Multivariate Analysis
Functional classification of ornamental stone using machine learning techniques
Journal of Computational and Applied Mathematics
A half-region depth for functional data
Computational Statistics & Data Analysis
Fuzzy data treated as functional data: A one-way ANOVA test approach
Computational Statistics & Data Analysis
The median of a random fuzzy number. The 1-norm distance approach
Fuzzy Sets and Systems
No effect tests in regression on functional variable and some applications to spectrometric studies
Computational Statistics
Bootstrap confidence sets for the Aumann mean of a random closed set
Computational Statistics & Data Analysis
| Hi-index | 0.03 |
The bootstrap methodology for functional data and functional estimation target is considered. A Monte Carlo study analyzing the performance of the bootstrap confidence bands (obtained with different resampling methods) of several functional estimators is presented. Some of these estimators (e.g., the trimmed functional mean) rely on the use of depth notions for functional data and do not have received yet much attention in the literature. A real data example in cardiology research is also analyzed. In a more theoretical aspect, a brief discussion is given providing some insights on the asymptotic validity of the bootstrap methodology when functional data, as well as a functional parameter, are involved.