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Clustering Functional Data on Convex Function Spaces
2016The curves in a functional data set often present a variety of distinctive patterns corresponding to different shapes that can be identified by clustering the functions. However, clustering functional data is a difficult task because the function space is, generally, of infinite dimension.
DI BATTISTA, Tonio +2 more
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1994
The types of circuits used in data processing differ significantly from the signal processing functions presented in the previous chapters. Data processing functions typically perform calculations on numerical data, and considerations must be given to how the data is represented and to the speed at which it can be processed. For more complex functions,
Douglas E. Ott, Thomas J. Wilderotter
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The types of circuits used in data processing differ significantly from the signal processing functions presented in the previous chapters. Data processing functions typically perform calculations on numerical data, and considerations must be given to how the data is represented and to the speed at which it can be processed. For more complex functions,
Douglas E. Ott, Thomas J. Wilderotter
openaire +1 more source
2012
Statistics is concerned with obtaining information from observations X 1, X 2, …, X N . The X n can be scalars, vectors or other objects. For example, each X n can be a satellite image, in some spectral bandwidth, of a particular region of the Earth taken at time n.
Lajos Horváth, Piotr Kokoszka
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Statistics is concerned with obtaining information from observations X 1, X 2, …, X N . The X n can be scalars, vectors or other objects. For example, each X n can be a satellite image, in some spectral bandwidth, of a particular region of the Earth taken at time n.
Lajos Horváth, Piotr Kokoszka
openaire +1 more source
An overview of real‐world data sources for oncology and considerations for research
Ca-A Cancer Journal for Clinicians, 2022Lynne Penberthy +2 more
exaly
2006
In many different fields of applied statistics the object of interest is depending on some continuous parameter, i.e. continuous time. Typical examples in biostatistics are growth curves or temperature measurements. Although for technical reasons, we are able to measure temperature just in discrete intervals — it is clear that temperature is a ...
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In many different fields of applied statistics the object of interest is depending on some continuous parameter, i.e. continuous time. Typical examples in biostatistics are growth curves or temperature measurements. Although for technical reasons, we are able to measure temperature just in discrete intervals — it is clear that temperature is a ...
openaire +1 more source
Functional genomics data: privacy risk assessment and technological mitigation
Nature Reviews Genetics, 2021Gamze Gürsoy, Tianxiao Li, Susanna Liu
exaly
Functional precision oncology using patient-derived assays: bridging genotype and phenotype
Nature Reviews Clinical Oncology, 2023Emile E Voest
exaly