Results 261 to 270 of about 12,934,423 (302)

An Analysis for Compounded Functions of Categorical Data

Biometrics, 1973
One area of application which has become increasingly important to statisticians and other researchers is the analysis of categorical data. Often the principal objective in such investigations is either the testing of appropriate hypotheses or the fitting of simplified models to the multi-dimensional contingency tables which arise when frequency counts
R N, Forthofer, G G, Koch
openaire   +2 more sources

Sparseness and functional data analysis

Oxford Handbooks Online, 2018
This article considers two functional data analysis settings where sparsity becomes important: the first involves only measurements at a relatively sparse set of points and the second relates to variable selection in a functional case.
Gareth M. James
semanticscholar   +1 more source

Functional Data Analysis and Its Application

2007
In this paper, we deal with functional data analysis including functional clustering and an application of functional data analysis. Functional data analysis is proposed by Ramsay et al. In functional data analysis, observed objects are represented by functions.
Masahiro Mizuta, June Kato
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Function Estimation and Functional Data Analysis

1994
The roughness penalty method is widely used in function estimation, and is closely related to methods of regularization well known in numerical analysis. Some background to the development of this method is discussed. The versatility of the method is illustrated by its application to an unusual smoothing problem, involving the estimation of a branching
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Empirical Dynamics and Functional Data Analysis

2010
We review some recent developments on modeling and estimation of dynamic phenomena within the framework of Functional Data Analysis (FDA). The focus is on longitudinal data which correspond to sparsely and irregularly sampled repeated measurements that are contaminated with noise and are available for a sample of subjects. A main modeling assumption is
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Functional Data Analysis for Spectroscopy Data

2020
We propose a functional data analysis approach for the study of spectroscopy data. The applicative problem concerns the characterization of the spectral response of silicate glasses in order to infer the chemical composition of the materials from spectral data, which can be remotely collected.
M. S. Bernardi, M. Fontana, A. Menafoglio, D. Perugini, A. Pisello, M. Ferrari, S. De Angelis, M. C. De Sanctis, S. Vantini   +8 more
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Functional Data Analysis for Sparse Longitudinal Data

, 2005
Fang Yao, H. Müller, Jane-ling Wang
semanticscholar   +1 more source

Functional Data Analysis

Journal of Educational and Behavioral Statistics, 1999
Eiji Muraki, J. O. Ramsay, B. W. Silverman   +2 more
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Nonparametric Functional Data Analysis: Theory And Practice

Technometrics, 2007
Z. John Lu
semanticscholar   +1 more source

Applied Functional Data Analysis

Technometrics, 2003
openaire   +1 more source