As an important exploratory analysis, curves of similar shape are often classified into groups, which we call clustering of functional data. Phase variations or time distortions are often encountered in the biological processes, such as growth patterns or gene profiles. As a result of time distortion, curves of similar shape may not be aligned. Regular clustering methods for functional data usually ignore the presence of phase variations, which may result in low clustering accuracy. However, it is difficult to account for phase variation without knowing the cluster structure. In this dissertation, we first propose a Bayesian method that simultaneously clusters and registers functional data. We model a warping function with a discrete approx...
Gene expression over time is, biologically, a continuous process and can thus be represented by a co...
International audienceWe propose a method for high-dimensional curve clustering in the presence of i...
The clustering for functional data with misaligned problems has drawn much attention in the last dec...
As an important exploratory analysis, curves of similar shape are often classified into groups, whic...
Functional data analysis aims to provide statistical inference for stochastic processes defined over...
When functional data come as multiple curves per subject, characterizing the source of variations is...
We develop a new method to locally cluster curves and discover functional motifs, i.e.~typical ``sha...
Phase variation in functional data obscures the true amplitude variation when a typical cross-sectio...
Our work is motivated by an analysis of elephant seal dive profiles which we view as functional data...
In many subjects such as psychology, geography, physiology or behavioral science, researchers collec...
A functional clustering (FC) method, "k"-centres FC, for longitudinal data is proposed. The "k"-cent...
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves me...
This thesis provides novel methodologies for functional Principal Component Analysis of dependent t...
Functional data usually consist of a sample of functions, with each function observed on a discrete ...
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves me...
Gene expression over time is, biologically, a continuous process and can thus be represented by a co...
International audienceWe propose a method for high-dimensional curve clustering in the presence of i...
The clustering for functional data with misaligned problems has drawn much attention in the last dec...
As an important exploratory analysis, curves of similar shape are often classified into groups, whic...
Functional data analysis aims to provide statistical inference for stochastic processes defined over...
When functional data come as multiple curves per subject, characterizing the source of variations is...
We develop a new method to locally cluster curves and discover functional motifs, i.e.~typical ``sha...
Phase variation in functional data obscures the true amplitude variation when a typical cross-sectio...
Our work is motivated by an analysis of elephant seal dive profiles which we view as functional data...
In many subjects such as psychology, geography, physiology or behavioral science, researchers collec...
A functional clustering (FC) method, "k"-centres FC, for longitudinal data is proposed. The "k"-cent...
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves me...
This thesis provides novel methodologies for functional Principal Component Analysis of dependent t...
Functional data usually consist of a sample of functions, with each function observed on a discrete ...
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves me...
Gene expression over time is, biologically, a continuous process and can thus be represented by a co...
International audienceWe propose a method for high-dimensional curve clustering in the presence of i...
The clustering for functional data with misaligned problems has drawn much attention in the last dec...