Results 21 to 30 of about 3,667,449 (266)
PLS classification of functional data [PDF]
Computational Statistics, 2007 Linear discriminant analysis (LDA) is considered when the predictor is of functional type (\(L_2\) stochastic process). The partial least squares (PLS) approach is used for dimension reduction before LDA. Estimates of the discriminant coefficient functions and discriminant scores are proposed.
Preda, Cristian +2 more
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Local linear approach: Conditional density estimate for functional and censored data
Demonstratio Mathematica, 2022 Let YY be a random real response, which is subject to right censoring by another random variable CC. In this paper, we study the nonparametric local linear estimation of the conditional density of a scalar response variable and when the covariable takes ...
Benkhaled Abdelkader, Madani Fethi
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Mathematics, 2022 Functional data analysis has important applications in biomedical, health studies and other areas. In this paper, we develop a general framework for a mean curve estimation for functional data using a reproducing kernel Hilbert space (RKHS) and derive ...
Ming Xiong +4 more
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A Distance Correlation Approach for Optimum Multiscale Selection in 3D Point Cloud Classification
Mathematics, 2021 Supervised classification of 3D point clouds using machine learning algorithms and handcrafted local features as covariates frequently depends on the size of the neighborhood (scale) around each point used to determine those features.
Manuel Oviedo-de la Fuente +3 more
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Differential Privacy for Functions and Functional Data
CoRR, 2012 Differential privacy is a framework for privately releasing summaries of a database. Previous work has focused mainly on methods for which the output is a finite dimensional vector, or an element of some discrete set. We develop methods for releasing functions while preserving differential privacy.
Rob Hall 0001 +2 more
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The K Nearest Neighbors Estimation of the Conditional Hazard Function for Functional Data
Revstat Statistical Journal, 2014 In this paper, we study the nonparametric estimator of the conditional hazard function using the k nearest neighbors (k-NN) estimation method for a scalar response variable given a random variable taking values in a semi-metric space. We give the almost
Mohammed Kadi Attouch +1 more
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Dynamic Functional Principal Components for Testing Causality
Signals, 2021 In this paper, we investigate the causality in the sense of Granger for functional time series. The concept of causality for functional time series is defined, and a statistical procedure of testing the hypothesis of non-causality is proposed.
Matthieu Saumard, Bilal Hadjadji
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Online EM for functional data [PDF]
Computational Statistics & Data Analysis, 2017 A novel approach to perform unsupervised sequential learning for functional data is proposed. Our goal is to extract reference shapes (referred to as templates) from noisy, deformed and censored realizations of curves and images. Our model generalizes the Bayesian dense deformable template model (Allassonnière et al., 2007), a hierarchical model in ...
Florian Maire +2 more
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Spatial prediction of soil infiltration using functional geostatistics
Acta Universitatis Carolinae Geographica, 2018 The infiltration of water into the soil is a necessary parameter for irrigation systems design. Characterizing its spatial behavior allows a site-specific management of water according to soil conditions and crop requirements. The aim of this study is to
Diego Leonardo Cortes-D +2 more
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Models of Functional Neuroimaging Data [PDF]
Current Medical Imaging Reviews, 2006 Inferences about brain function, using functional neuroimaging data, require models of how the data were caused. A variety of models are used in practice that range from conceptual models of functional anatomy to nonlinear mathematical models of hemodynamic responses (e.g.
Stephan, K E +3 more
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