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Initial Steps towards a Multilevel Functional Principal Components Analysis Model of Dynamical Shape Changes [PDF]

Journal of Imaging, 2023
In this article, multilevel principal components analysis (mPCA) is used to treat dynamical changes in shape. Results of standard (single-level) PCA are also presented here as a comparison. Monte Carlo (MC) simulation is used to create univariate data (i.
Damian J. J. Farnell, Peter Claes
doaj   +2 more sources

Functional principal components analysis of workload capacity functions. [PDF]

Behav Res Methods, 2013
Workload capacity, an important concept in many areas of psychology, describes processing efficiency across changes in workload. The capacity coefficient is a function across time that provides a useful measure of this construct. Until now, most analyses of the capacity coefficient have focused on the magnitude of this function, and often only in terms
Burns DM, Houpt JW, Townsend JT, Endres MJ.   +3 more
europepmc   +4 more sources

Contrastive Functional Principal Components Analysis. [PDF]

Proc AAAI Conf Artif Intell
As functional data assumes a central role in contemporary data analysis, the search for meaningful dimension reduction becomes critical due to its inherent infinite-dimensional structure. Traditional methods, such as Functional Principal Component Analysis (FPCA), adeptly explore the overarching structures within the functional data.
Zhang E, Li D.
europepmc   +2 more sources

Calciumnetexplorer: an R package for network analysis of calcium imaging data [PDF]

BMC Bioinformatics
Background Analyzing calcium imaging data to understand complex functional networks can be challenging, often requiring multiple tools, custom scripts, and some coding expertise.
Simone Lenci, Dirk Sieger
doaj   +2 more sources

Optimal Estimation of Large Functional and Longitudinal Data by Using Functional Linear Mixed Model

Mathematics, 2022
The estimation of large functional and longitudinal data, which refers to the estimation of mean function, estimation of covariance function, and prediction of individual trajectory, is one of the most challenging problems in the field of high ...
Mengfei Ran, Yihe Yang
doaj   +1 more source

Machine-Learning-Based Functional Time Series Forecasting: Application to Age-Specific Mortality Rates

Forecasting, 2022
We propose a functional time series method to obtain accurate multi-step-ahead forecasts for age-specific mortality rates. The dynamic functional principal component analysis method is used to decompose the mortality curves into dynamic functional ...
Ufuk Beyaztas, Hanlin Shang
doaj   +1 more source

Functional data analysis: Application to daily observation of COVID-19 prevalence in France

AIMS Mathematics, 2022
In this paper we use the technique of functional data analysis to model daily hospitalized, deceased, Intensive Care Unit (ICU) cases and return home patient numbers along the COVID-19 outbreak, considered as functional data across different departments ...
Kayode Oshinubi, Firas Ibrahim , Mustapha Rachdi, Jacques Demongeot   +3 more
doaj   +1 more source

Longitudinal functional principal component analysis [PDF]

Electronic Journal of Statistics, 2010
We introduce models for the analysis of functional data observed at multiple time points. The dynamic behavior of functional data is decomposed into a time-dependent population average, baseline (or static) subject-specific variability, longitudinal (or dynamic) subject-specific variability, subject-visit-specific variability and measurement error. The
Greven, Sonja, Crainiceanu, Ciprian, Caffo, Brian, Reich, Daniel   +3 more
openaire   +3 more sources

Wildfires Vegetation Recovery through Satellite Remote Sensing and Functional Data Analysis

Mathematics, 2021
In recent years, wildfires have caused havoc across the world, which are especially aggravated in certain regions due to climate change. Remote sensing has become a powerful tool for monitoring fires, as well as for measuring their effects on vegetation ...
Feliu Serra-Burriel, Pedro Delicado, Fernando M. Cucchietti   +2 more
doaj   +1 more source

Structured Functional Principal Component Analysis [PDF]

Biometrics, 2014
Summary Motivated by modern observational studies, we introduce a class of functional models that expand nested and crossed designs. These models account for the natural inheritance of the correlation structures from sampling designs in studies where the fundamental unit is a function or image. Inference is based on functional quadratics
Shou, Haochang, Zipunnikov, Vadim, Crainiceanu, Ciprian M., Greven, Sonja   +3 more
openaire   +4 more sources