Results 51 to 60 of about 33,054,453 (365)
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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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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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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Rank dynamics for functional data
Computational Statistics & Data Analysis, 2020 The study of the dynamic behavior of cross-sectional ranks over time for functional data and the ranks of the observed curves at each time point and their temporal evolution can yield valuable insights into the time dynamics of functional data. This approach is of interest in various application areas.
Yaqing Chen 0003 +2 more
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Asymptotic properties of penalized splines for functional data
, 2020 Penalized spline methods are popular for functional data analysis but their asymptotic properties have not been developed. We present a theoretic study of the L2 and uniform convergence of penalized spline estimators for estimating the mean and ...
Luo Xiao
semanticscholar +1 more source
From data to function: Functional modeling of poultry genomics data
Poultry Science, 2013 One of the challenges of functional genomics is to create a better understanding of the biological system being studied so that the data produced are leveraged to provide gains for agriculture, human health, and the environment. Functional modeling enables researchers to make sense of these data as it reframes a long list of genes or gene products ...
F M, McCarthy, E, Lyons
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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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A Comparison of Spatiotemporal and Functional Kriging Approaches
, 2021 Here we present and compare functional and spatiotemporal (Sp.T.) kriging approaches to predict spatial functional random processes, which can also be viewed as Sp.T. random processes. Comparisons are focused on Sp.T.
Sjöstedt de Luna, Sara, +5 more
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