Results 1 to 10 of about 14,309 (209)
Kriging and Prediction of Nonlinear Functionals
Austrian Journal of Statistics, 2016 The prediction of a nonlinear functional of a random field is studied. The covariance-matching constrained kriging is considered. It is proved that the optimization problem induced by it always has a solution. The proof is constructive and it provides an
Alexander Kukush, István Fazekas
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An Overview of Kriging and Cokriging Predictors for Functional Random Fields
Mathematics, 2023 This article presents an overview of methodologies for spatial prediction of functional data, focusing on both stationary and non-stationary conditions.
Ramón Giraldo +2 more
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Separation Reliability Analysis for the Low-Shock Separation Nut with Mechanism Motion Failure Mode
Aerospace, 2022 A functional reliability simulation method based on the Kriging model is proposed to efficiently evaluate the functional reliability of low-shock separation nuts.
Lei Niu +3 more
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Kriging with Nonparametric Variance Function Estimation [PDF]
Biometrics, 1999 Summary. A method for fitting regression models to data that exhibit spatial correlation and heteroskedas‐ticity is proposed. It is well known that ignoring a nonconstant variance does not bias least‐squares estimates of regression parameters; thus, data analysts are easily lead to the false belief that moderate heteroskedas‐ticity can generally be ...
Opsomer, Jean +4 more
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Sparse estimation in kriging for functional data
Stochastic Environmental Research and Risk Assessment, 2023 We introduce a sparse estimation in the ordinary kriging for functional data. The functional kriging predicts a feature given as a function at a location where the data are not observed by a linear combination of data observed at other locations. To estimate the weights of the linear combination, we apply the lasso-type regularization in minimizing the
Hidetoshi Matsui +2 more
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Sliced Gradient-Enhanced Kriging for High-Dimensional Function Approximation
SIAM Journal on Scientific Computing, 2023 Gradient-enhanced Kriging (GE-Kriging) is a well-established surrogate modelling technique for approximating expensive computational models. However, it tends to get impractical for high-dimensional problems due to the size of the inherent correlation matrix and the associated high-dimensional hyper-parameter tuning problem.
Kai Cheng, Ralf Zimmermann
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Functional Kriging for Spatiotemporal Modeling of Nitrogen Dioxide in a Middle Eastern Megacity
Atmosphere, 2022 Long-term hour-specific air pollution exposure estimates have rarely been of interest in epidemiological research. However, this can be relevant for studies that aim to estimate the residential exposure for the hours that subjects mostly spend time there,
Elham Ahmadi Basiri +3 more
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Anomaly detection in geostatistical models with application to groundwater level data in the Gaza Coastal Aquifer [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2022 In geostatistics, the detection of anomalous observations has a particular importance because of the changes they can create in environmental and geological patterns. Few methods for detecting such observations in univariate data have been proposed for
Ali H. Abuzaid +2 more
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Frontiers in Plant Science, 2023 The relationship between plant functional traits and ecosystem function is a hot topic in current ecological research, and community-level traits based on individual plant functional traits play important roles in ecosystem function.
Yudong Chen +20 more
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D-STEM v2: A Software for Modeling Functional Spatio-Temporal Data
Journal of Statistical Software, 2021 Functional spatio-temporal data naturally arise in many environmental and climate applications where data are collected in a three-dimensional space over time.
Yaqiong Wang +2 more
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