Everything about Functional data analysis
Branch of statistics mathematics
Functional data analysis (FDA) is a branch of statistics that analyses data providing information about curves, surfaces or anything else varying over a continuum. In its most general form, under an FDA framework, each sample element of functional data is considered to be a random function. The physical continuum over which these functions are defined is often time, but may also be spatial location, wavelength, probability, etc. Intrinsically, functional data are infinite dimensional. The high intrinsic dimensionality of these data brings challenges for theory as well as computation, where these challenges vary with how the functional data were sampled. However, the high or infinite dimensional structure of the data is a rich source of information and there are many interesting challenges for research and data analysis. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Functional data analysisA 5-minute orientation
- Skim a recent paper: The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interestInfluential work since 2022
- Pick up a classic book: Statistical Analysis Of Fmri DataThe most-reprinted book on the subject
- Read the landmark paper: Functional Data Analysis for Sparse Longitudinal DataCited 1,335 times
- Go sideways: Functional regressionA closely related topic
- Go sideways: Functional correlationA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Functional Data Analysis for Sparse Longitudinal Data
Functional Data Analysis
Some Tools for Functional Data Analysis
Functional data analysis for volatility
Introduction to functional data analysis.
Longitudinal functional data analysis
Intrinsic Riemannian functional data analysis
Linear discriminant analysis for multiple functional data analysis
🆕 Influential since 2022
The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest
On functional data analysis and related topics
Data driven orthogonal basis selection for functional data analysis
Functional data analysis using deep neural networks
Acoustic seascape partitioning through functional data analysis
📚 Books worth reading
Statistical Analysis Of Fmri DataF. Gregory Ashby · 2011
MatLab® Companion to Complex VariablesA. David Wunsch · 2016
KERNEL METHODS FOR PATTERN ANALYSISJOHN SHAWE-TAYLOR, John Shawe-Taylor · 2004
CalculusHarley Flanders · 1970
Elementary FunctionsJean-Michel Muller · 2005- 📕Image Processing Tour of College MathematicsYevgeniy V. Galperin · 2021
Posthumanism and Deconstructing ArgumentsKieran O'Halloran · 2017
The best approximation methodTheodore V. Hromadka, Chung-Cheng Yen · 1987
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Functional regression Functional regression is a version of regression analysis when responses or covariates include functional data. Functional regression models can be classified…
- Functional correlation In statistics, functional correlation is a dimensionality reduction technique used to quantify the correlation and dependence between two variables when…
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- History index model In statistical analysis, the standard framework of varying coefficient models (also known as concurrent regression models), where the current value of…
- Distributional data analysis Distributional data analysis is a branch of nonparametric statistics that is related to functional data analysis. It is concerned with random objects that…
- High-dimensional statistics In statistical theory, the field of high-dimensional statistics studies data whose dimension is larger (relative to the number of datapoints) than typically…
- Generalized functional linear model The generalized functional linear model (GFLM) is an extension of the generalized linear model (GLM) that allows one to regress univariate responses of…
- Logistic regression In statistics, a logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent…