Geostatistics for functional data: an ordinary kriging approach
We present a methodology to perform spatial prediction when measured data are curves. In particular, we propose both an estimator of the spatial correlation and a functional kriging predictor. We adapt an optimization criterium used in multi- variable spatial prediction in order to estimate the kriging parameters.
Giraldo, Ramón +2 more
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A neural network-based automatic semi-variogram modeling approach for geomagnetic map construction in multi-source indoor and outdoor navigation. [PDF]
Zhan C, Huang P, Xue B, Lan B.
europepmc +1 more source
Optimal interpolation methods for predicting groundwater levels in Abu Dhabi Emirate using ArcGIS. [PDF]
Maksoud T, Alkhawaga A, Mohamed M.
europepmc +1 more source
Integrating random forest-based regression kriging for analyzing spatial variability of rainfall in arid and semi-arid regions. [PDF]
Manaf M, Ali Z, Scholz M.
europepmc +1 more source
GEOTrat Points as a free resource in QGIS for mapping the performance of agricultural experiments. [PDF]
Xavier LCM +3 more
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Lognormal Ordinary Kriging Metamodel in Simulation Optimization
Muzaffer Balaban, Berna Dengiz
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Mapping intracellular dynamics across the whole cell with spatial statistics. [PDF]
Okabe Y +4 more
europepmc +1 more source
AI-enhanced clustering of mine tailings using Geostatistical data augmentation and Gaussian mixture models. [PDF]
Madani N, Sabanov S.
europepmc +1 more source

