Functional data analysis (FDA) is a statistical framework that allows for the analysis of
curves, images, or functions on higher dimensional domains. The goals of FDA, such as …

Discovering causal relationship using multivariate functional data has received a significant
amount of attention very recently. In this article, we introduce a functional linear structural …

Mendelian randomization is an instrumental variable method that utilizes genetic information
to investigate the causal effect of a modifiable exposure on an outcome. In most cases, the …

Analyzing longitudinal data in health studies is challenging due to sparse and error‐prone
measurements, strong within‐individual correlation, missing data and various trajectory …

Digital health technologies such as wearable devices have transformed health data
analytics, providing continuous, high-resolution functional data on various health metrics …

We propose a new method for estimating subject-specific mean functions from longitudinal
data. We aim to do this in a flexible manner (without restrictive assumptions about the shape …

Mendelian randomization is an epidemiological method that uses genetic variants as
instrumental variables to study the causal effects of exposures on outcomes. Conventional …

In clinical practice and biomedical research, measurements are often collected sparsely and
irregularly in time, while the data acquisition is expensive and inconvenient. Examples …