Results 21 to 30 of about 7,564,642 (290)
Bayesian function‐on‐function regression for multilevel functional data [PDF]
SummaryMedical and public health research increasingly involves the collection of complex and high dimensional data. In particular, functional data—where the unit of observation is a curve or set of curves that are finely sampled over a grid—is frequently obtained.
Meyer, Mark J +4 more
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Combining Entropy Measures for Anomaly Detection
The combination of different sources of information is a problem that arises in several situations, for instance, when data are analysed using different similarity measures.
Alberto Muñoz +3 more
doaj +1 more source
Local linear approach: Conditional density estimate for functional and censored data
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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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
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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Functional Multi-Layer Perceptron: a Nonlinear Tool for Functional Data Analysis [PDF]
In this paper, we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional MLP.
Abraham +32 more
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Dynamic Functional Principal Components for Testing Causality
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
doaj +1 more source
The K Nearest Neighbors Estimation of the Conditional Hazard Function for Functional Data
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
doaj +1 more source
Models of Functional Neuroimaging Data [PDF]
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
openaire +2 more sources
Spatial prediction of soil infiltration using functional geostatistics
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
doaj +1 more source

