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Functional Data Analysis for Sparse Functional Data
2018With 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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2001
Most statistical analyses involve one or more observations taken on each of a number of individuals in a sample, with the aim of making inferences about the general population from which the sample is drawn. In an increasing number of fields, these observations are curves or images.
Silverman, BW, Ramsay, JO
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Most statistical analyses involve one or more observations taken on each of a number of individuals in a sample, with the aim of making inferences about the general population from which the sample is drawn. In an increasing number of fields, these observations are curves or images.
Silverman, BW, Ramsay, JO
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Repeated measures analysis for functional data
Computational Statistics & Data Analysis, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Pablo Martínez-Camblor, Norberto Corral
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An Analysis for Compounded Functions of Categorical Data
Biometrics, 1973One 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
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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 ...
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Function Estimation and Functional Data Analysis
1994The 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
2010We 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
2020We 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 +8 more
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