The mean function is a central object of inquiry in the analysis of functional data. Typical
questions related to the mean function include quantifying estimation uncertainty, testing …

Marketing research relies on individual-level estimates to understand the rich heterogeneity
of consumers, firms, and products. While much of the literature focuses on capturing static …

With the rapid development of science, technology, and engineering, large amounts of data
have been generated in many fields in the past 20 years. In the process of medical research …

In many applications, smooth processes generate data that are recorded under a variety of
observational regimes, including dense sampling and sparse or fragmented observations …

Evaluation of the cooling trend in the ionosphere using functional regression with incomplete curves
Page 1 The Annals of Applied Statistics 2017, Vol. 11, No. 2, 898–918 DOI: 10.1214/17-AOAS1022 …

Recent development of the quick contrast sensitivity function (qCSF) method has made it
possible to obtain accurate, precise, and efficient contrast sensitivity function (CSF) …

Multi-dimensional functional data arises in numerous modern scientific experimental and
observational studies. In this article, we focus on longitudinal functional data, a structured …

Purpose: The goal of this study is to develop a hierarchical Bayesian model (HBM) to better
quantify uncertainty in visual acuity (VA) tests by incorporating the relationship between VA …

High juvenile mortality rates are typical of many long‐lived marine vertebrate predators.
Insufficient development in dive and forage ability is considered a key driver of this …

A novel multi-task Gaussian process (GP) framework is proposed, by using a common mean
process for sharing information across tasks. In particular, we investigate the problem of time …