Results 11 to 20 of about 33,300,374 (339)
Functional Data Analysis: An Introduction and Recent Developments [PDF]
Biometrical journal. Biometrische Zeitschrift, 2023 Functional data analysis (FDA) is a statistical framework that allows for the analysis of curves, images, or functions on higher dimensional domains. The goals of FDA, such as descriptive analyses, classification, and regression, are generally the same ...
Jan Gertheiss +3 more
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scikit-fda: A Python Package for Functional Data Analysis [PDF]
Journal of Statistical Software, 2022 The library scikit-fda is a Python package for Functional Data Analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data.
Carlos Ramos-Carreño +4 more
semanticscholar +1 more source
Review of Clustering Methods for Functional Data [PDF]
ACM Transactions on Knowledge Discovery from Data, 2022 Functional data clustering is to identify heterogeneous morphological patterns in the continuous functions underlying the discrete measurements/observations.
Mimi Zhang, Andrew C. Parnell
semanticscholar +1 more source
Second-Generation Functional Data
Annual Review of Statistics and Its Application, 2023 Modern studies from a variety of fields record multiple functional observations according to either multivariate, longitudinal, spatial, or time series designs.
Salil Koner, A. Staicu
semanticscholar +1 more source
Nucleic Acids Res., 2022 Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across ...
Damian Szklarczyk +12 more
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Recent developments in complex and spatially correlated functional data [PDF]
Brazilian Journal of Probability and Statistics, 2020 As high-dimensional and high-frequency data are being collected on a large scale, the development of new statistical models is being pushed forward. Functional data analysis provides the required statistical methods to deal with large-scale and complex ...
Israel Mart'inez-Hern'adez, M. Genton
semanticscholar +1 more source
Copula Gaussian Graphical Models for Functional Data
Journal of the American Statistical Association, 2020 We introduce a statistical graphical model for multivariate functional data, which are common in medical applications such as EEG and fMRI. Recently published functional graphical models rely on the multivariate Gaussian process assumption, but we relax ...
Eftychia Solea, Bing Li
semanticscholar +1 more source
Weakly dependent functional data [PDF]
, 2010 Functional data often arise from measurements on fine time grids and are obtained by separating an almost continuous time record into natural consecutive intervals, for example, days.
Hörmann, Siegfried, Kokoszka, Piotr
core +1 more source
Bayesian Nonparametric Mixture Estimation for Time-Indexed Functional Data in R
Journal of Statistical Software, 2016 We present growfunctions for R that offers Bayesian nonparametric estimation models for analysis of dependent, noisy time series data indexed by a collection of domains.
Terrance D. Savitsky
doaj +1 more source
Risks, 2018 A functional ARMA-GARCH model for predicting the value-at-risk of the EURUSD exchange rate is introduced. The model implements the yield curve differentials between EUR and the US as exogenous factors. Functional principal component analysis allows us to
Holger Fink, Andreas Fuest, Henry Port
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