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Testing for the significance of functional covariates
Journal of Multivariate Analysis, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Maistre, Samuel, Patilea, Valentin
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Random forests for functional covariates
Journal of Chemometrics, 2016We propose a form of random forests that is especially suited for functional covariates. The method is based on partitioning the functions' domain in intervals and using the functions' mean values across those intervals as predictors in regression or classification trees.
Möller, Annette Christine +2 more
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Modern Physics Letters A, 1993
The differential realization of the recently proposed deformed Poincaré algebra is considered. The notion of covariant wave functions is introduced and their explicit form in the "minimal" (in Weinberg's sense) case is given. The deformed Dirac equation is constructed.
S. GILLER +5 more
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The differential realization of the recently proposed deformed Poincaré algebra is considered. The notion of covariant wave functions is introduced and their explicit form in the "minimal" (in Weinberg's sense) case is given. The deformed Dirac equation is constructed.
S. GILLER +5 more
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On Covariance Functions of Unit Processes
SIAM Journal on Applied Mathematics, 1972The problem of meaningful characterization of the covariance functions, “unit covariances,” of two-valued stationary stochastic processes is considered. Some general properties are derived. For some broad classes of unit covariances, corresponding to two-valued processes with a specified structure of axis crossing, complete and explicit ...
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Which parameterization of the Matérn covariance function?
Spatial Statistics, 2023The Matérn family of covariance functions is currently the most popularly used model in spatial statistics, geostatistics, and machine learning to specify the correlation between two geographical locations based on spatial distance. Compared to existing covariance functions, the Matérn family has more flexibility in data fitting because it allows the ...
Wang, Kesen +3 more
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On Some Characteristics of Gaussian Covariance Functions
International Statistical Review, 2020SummaryThe concepts of isotropy/anisotropy and separability/non‐separability of a covariance function are strictly related. If a covariance function is separable, it cannot be isotropic or geometrically anisotropic, except for the Gaussian covariance function, which is the only model both separable and isotropic. In this paper, some interesting results
De Iaco, Sandra +3 more
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When is a truncated covariance function on the line a covariance function on the circle?
Statistics & Probability Letters, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Bulletin Géodésique, 1987
Because of the full covariance matrices and the computer storage limitations the number of measurements which can be handled by the collocation method simultaneously, is limited. This paper presents a method to compute covariance functions with a finite support yielding sparse covariance matrices.
F. Sansò, W. -D. Schuh
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Because of the full covariance matrices and the computer storage limitations the number of measurements which can be handled by the collocation method simultaneously, is limited. This paper presents a method to compute covariance functions with a finite support yielding sparse covariance matrices.
F. Sansò, W. -D. Schuh
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A NONPARAMETRIC ESTIMATOR FOR THE COVARIANCE FUNCTION OF FUNCTIONAL DATA
Econometric Theory, 2014Many quantities of interest in economics and finance can be represented as partially observed functional data. Examples include structural business cycle estimation, implied volatility smile, the yield curve. Having embedded these quantities into continuous random curves, estimation of the covariance function is needed to extract factors, perform ...
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The Characterization Problem for Isotropic Covariance Functions
Mathematical Geology, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gneiting, Tilmann, Sasvári, Zoltán
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