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 …
Longitudinal functional data analysis
SY Park, AM Staicu - Stat, 2015 - Wiley Online Library
We consider dependent functional data that are correlated because of a longitudinal‐based
design: each subject is observed at repeated times and at each time, a functional …
design: each subject is observed at repeated times and at each time, a functional …
Layer-wise spatial modeling of porosity in additive manufacturing
The objective of this work is to model and quantify the layer-wise spatial evolution of porosity
in parts made using Additive Manufacturing (AM) processes. This is an important research …
in parts made using Additive Manufacturing (AM) processes. This is an important research …
Nonlinear and additive principal component analysis for functional data
We introduce a nonlinear additive functional principal component analysis (NAFPCA) for
vector-valued functional data. This is a generalization of functional principal component …
vector-valued functional data. This is a generalization of functional principal component …
[HTML][HTML] A nonparametric penalized likelihood approach to density estimation of space-time point patterns
In this work, we consider space-time point processes and study their continuous space-time
evolution. We propose an innovative nonparametric methodology to estimate the unknown …
evolution. We propose an innovative nonparametric methodology to estimate the unknown …
Bayesian semiparametric functional mixed models for serially correlated functional data, with application to glaucoma data
W Lee, MF Miranda, P Rausch… - Journal of the …, 2019 - Taylor & Francis
Glaucoma, a leading cause of blindness, is characterized by optic nerve damage related to
intraocular pressure (IOP), but its full etiology is unknown. Researchers at UAB have …
intraocular pressure (IOP), but its full etiology is unknown. Researchers at UAB have …
Modeling time-varying random objects and dynamic networks
Samples of dynamic or time-varying networks and other random object data such as time-
varying probability distributions are increasingly encountered in modern data analysis …
varying probability distributions are increasingly encountered in modern data analysis …
Statistical modeling of spatial big data: An approach from a functional data analysis perspective
R Giraldo, S Dabo-Niang, S Martinez - Statistics & Probability Letters, 2018 - Elsevier
Statistical modeling of spatial big data: An approach from a functional data analysis perspective
- ScienceDirect Skip to main contentSkip to article Elsevier logo Journals & Books Search …
- ScienceDirect Skip to main contentSkip to article Elsevier logo Journals & Books Search …
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 …
Exploring patterns of demand in bike sharing systems via replicated point process models
Understanding patterns of demand is fundamental for fleet management of bike sharing
systems. We analyse data from the Divvy system of the city of Chicago. We show that the …
systems. We analyse data from the Divvy system of the city of Chicago. We show that the …