Results 141 to 150 of about 7,590,878 (189)

Clustering Functional Data

Journal of Classification, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tarpey, Thaddeus, Kinateder, Kimberly
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Cluster non‐Gaussian functional data

Biometrics, 2020
AbstractGaussian distributions have been commonly assumed when clustering functional data. When the normality condition fails, biased results will follow. Additional challenges occur as the number of the clusters is often unknown a priori. This paper focuses on clustering non‐Gaussian functional data without the prior information of the number of ...
Qingzhi Zhong, Huazhen Lin, Yi Li
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Statistics for Functional Data

Computational Statistics & Data Analysis, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gonzalez Manteiga, Wenceslao, Vieu, Philippe   +1 more
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Integrating functional genomics data

Biochemical Society Transactions, 2003
Functional annotation of fully sequenced genomes is still a major issue. High-throughput data sets could be used to provide more and better functional annotations. However differences in data quality need to be taken into account. For this purpose these high-throughput data sets need to be integrated so that the data quality can be assessed, hypotheses
P, Kemmeren, F C P, Holstege
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Integrating Functional Genomics Data

2008
The revolution in high throughput biology experiments producing genome-scale data has heightened the challenge of integrating functional genomics data. Data integration is essential for making reliable inferences from functional genomics data, as the datasets are neither error-free nor comprehensive.
Insuk, Lee, Edward M, Marcotte
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Clustering Geostatistical Functional Data

2011
In this paper, we among functional data. A first strategy aims to classify curves spatially dependent and to obtain a spatio-functional model prototype for each cluster. It is based on a Dynamic Clustering Algorithm with on an optimization problem that minimizes the spatial variability among the curves in each cluster. A second one looks simultaneously
ROMANO, Elvira, VERDE, Rosanna
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Estimating the covariance function with functional data

British Journal of Mathematical and Statistical Psychology, 2002
This paper describes a two‐step procedure for estimating the covariance function and its eigenvalues and eigenfunctions in situations where the data are curves or functions. The first step produces initial estimates of eigenfunctions using a standard principal components analysis.
Sik-Yum, Lee, Wenyang, Zhang, Xin-Yuan, Song   +2 more
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Functional Data Analysis for Sparse Functional Data

2018
With the development of science and modern technology, more and more data are being collected continuously over a time interval in various disciplines, such as public health, biology, medicine and finance. Such data can be viewed as ``functional data". Functional data analysis (FDA), which deals with the analysis and theory of functional data, has been
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Functional Data Structures

1996
A functional data structure is a data structure that is suitable for implementation in a functional programming language, or for coding in an ordinary language like C or Java using a functional style. Functional data structures are closely related to persistent data structures and immutable data structures—in fact, the three terms are often used ...
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A Depth Function for Geostatistical Functional Data

2015
In this paper we introduce a depth measure for geostatistical functional data. The aim is to provide a tool which allows to get a center-outward ordering of functional data recorded by sensors placed on a geographic area. Although the topic of ordering functional data has already been addressed in the literature, no proposal analyzes the case in which ...
BALZANELLA, Antonio, ROMANO, Elvira
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