Modeling Repeated Functional Observations

Modeling Repeated Functional Observations

We introduce a new methodological framework for repeatedly observed and thus dependent functional data, aiming at situations where curves are recorded repeatedly for each subject in a sample. Our methodology covers the case where the recordings of the curves are scheduled on a regular and dense grid and also situations more typical for longitudinal studies, where the timing of recordings is oft...

Modeling Repeated Functional Observations

We first state two auxiliary results that are useful for the theoretical arguments. One of these is a Bernstein-type concentration inequality (Del Barrio et al.

Repeated Measures and Multilevel Modeling

Statistical notes for clinical researchers: A one-way repeated measures ANOVA for data with repeated observations

91 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Statistical notes for clinical researchers: A one-way repeated measures ANOVA for data w...

Classiåcation of repeated observations based on the growth curve model

A classiåcation method for repeated observations is proposed. The method consists of two procedures. First, individual response proåles are åtted by the polynomial regression model. Next, the åtted regression coeécients are classiåed based on the normal mixture model. The procedures can be embedded in one model, i.e., the growth curve model with extended random eãects. It helps us to explore an...