Review of clustering methods for functional data
Functional data clustering is to identify heterogeneous morphological patterns in the
continuous functions underlying the discrete measurements/observations. Application of …
continuous functions underlying the discrete measurements/observations. Application of …
clusterBMA: Bayesian model averaging for clustering
Various methods have been developed to combine inference across multiple sets of results
for unsupervised clustering, within the ensemble clustering literature. The approach of …
for unsupervised clustering, within the ensemble clustering literature. The approach of …
A multivariate functional-data mixture model for spatio-temporal data: inference and cokriging
In this paper, we introduce a model for multivariate, spatio-temporal functional data.
Specifically, this work proposes a mixture model that is used to perform spatio-temporal …
Specifically, this work proposes a mixture model that is used to perform spatio-temporal …
Clustering spatially correlated functional data with multiple scalar covariates
H Wu, YF Li - IEEE Transactions on Neural Networks and …, 2022 - ieeexplore.ieee.org
We propose a probabilistic model for clustering spatially correlated functional data with
multiple scalar covariates. The motivating application is to partition the 29 provinces of the …
multiple scalar covariates. The motivating application is to partition the 29 provinces of the …
Dynamic and Static Enhanced BIRCH for Functional Data Clustering
W Li, H Li, Y Luo - IEEE Access, 2023 - ieeexplore.ieee.org
Accurate and efficient clustering of large-scale functional data is of utmost importance in the
era of big data. However, the current research falls short in fully considering the …
era of big data. However, the current research falls short in fully considering the …
Functional clustering methods for binary longitudinal data with temporal heterogeneity
In the analysis of binary longitudinal data, it is of interest to model a dynamic relationship
between a response and covariates as a function of time, while also investigating similar …
between a response and covariates as a function of time, while also investigating similar …
Penalized model-based clustering of complex functional data
N Pronello, R Ignaccolo, L Ippoliti, S Fontanella - Statistics and Computing, 2023 - Springer
High dimensional data, large-scale data, imaging and manifold data are all fostering new
frontiers of statistics. These type of data are commonly considered in Functional Data …
frontiers of statistics. These type of data are commonly considered in Functional Data …
Anatomically compliant modes of variations: New tools for brain connectivity
Anatomical complexity and data dimensionality present major issues when analysing brain
connectivity data. The functional and anatomical aspects of the connections taking place in …
connectivity data. The functional and anatomical aspects of the connections taking place in …
Introduction to Geostatistical Functional Data Analysis
This chapter aims to provide a general introduction to the relevant fields that will appear
along the individual chapters of the book. We first provide a general introduction to spatial …
along the individual chapters of the book. We first provide a general introduction to spatial …
A Bayesian functional PCA model with multilevel partition priors for group studies in neuroscience
The statistical analysis of group studies in neuroscience is particularly challenging due to
the complex spatio-temporal nature of the data, its multiple levels and the inter-individual …
the complex spatio-temporal nature of the data, its multiple levels and the inter-individual …