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 …
From multivariate to functional data analysis: Fundamentals, recent developments, and emerging areas
Functional data analysis (FDA), which is a branch of statistics on modeling infinite
dimensional random vectors resided in functional spaces, has become a major research …
dimensional random vectors resided in functional spaces, has become a major research …
Unveiling air pollution patterns in Yemen: a spatial–temporal functional data analysis
MA Hael - Environmental Science and Pollution Research, 2023 - Springer
The application of spatiotemporal functional analysis techniques in environmental pollution
research remains limited. As a result, this paper suggests spatiotemporal functional data …
research remains limited. As a result, this paper suggests spatiotemporal functional data …
Unified principal component analysis for sparse and dense functional data under spatial dependency
We consider spatially dependent functional data collected under a geostatistics setting,
where locations are sampled from a spatial point process. The functional response is the …
where locations are sampled from a spatial point process. The functional response is the …
Modeling spatial–temporal variability of PM2. 5 concentrations in Belt and Road Initiative (BRI) region via functional adaptive density approach
MA Hael - Environmental Science and Pollution Research, 2023 - Springer
The rapid development of the Belt and Road Initiative (BRI) has led to severe air pollution
dominated by PM2. 5 concentrations which can cause a profound negative impact on …
dominated by PM2. 5 concentrations which can cause a profound negative impact on …
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 …
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 …
Efficient and effective calibration of numerical model outputs using hierarchical dynamic models
We describe the details related to the proposed approach HDCM, including the datasets, the
competitive models, the selection of the tuning parameters, the simulation study for the …
competitive models, the selection of the tuning parameters, the simulation study for the …
Scanner: Simultaneously temporal trend and spatial cluster detection for spatial‐temporal data
Identifying the underlying trajectory pattern in the spatial‐temporal data analysis is a
fundamental but challenging task. In this paper, we study the problem of simultaneously …
fundamental but challenging task. In this paper, we study the problem of simultaneously …