A Universal Kriging predictor for spatially dependent functional data of a Hilbert Space [PDF]
, 2013 We address the problem of predicting spatially dependent functional data belonging to a Hilbert space, with a Functional Data Analysis approach. Having defined new global measures of spatial variability for functional random processes, we derive a ...
A. Menafoglio, M. Dalla Rosa, P. Secchi
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Spatio-Temporal Analysis of Drought Severity Using Drought Indices and Deterministic and Geostatistical Methods (Case Study: Zayandehroud River Basin) [PDF]
Desert, 2016 Drought monitoring is a fundamental component of drought risk management. It is normally performed using various drought indices that are effectively continuous functions of rainfall and other hydrometeorological variables.
A. Afzali +8 more
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Comparing Methods for Interpolation to Improve Raster Digital Elevation Models [PDF]
, 2012 Digital elevation models (DEMs) are available as raster files at 100m, 30m, and 10m resolutions for the contiguous United States and are used in a variety of geographic analyses. Some projects may require a finer resolution.
Guarneri, J. C., Weih, R. C., Jr.
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Climatic variations in Macerata province (Central Italy) [PDF]
, 2018 The province of Macerata, Italy, is a topographically complex region which has been little studied in terms of its temperature and precipitation climatology.
Barbieri, Maurizio +2 more
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Kernel Approximations for Universal Kriging Predictors
Journal of Multivariate Analysis, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, B., Stein, M.
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Augmenting Geostatistics with Matrix Factorization: A Case Study for House Price Estimation
ISPRS International Journal of Geo-Information, 2020 Singular value decomposition (SVD) is ubiquitously used in recommendation systems to estimate and predict values based on latent features obtained through matrix factorization.
Aisha Sikder, Andreas Züfle
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Regional scale surface of the top of the Variscan basement in the central sector of Italy
Journal of Maps, 2023 In this study, we combined regional geology and geostatistical analytical processing to model the top surface of the Variscan basement in Italy. This surface, which is overlain by the pre-Alpine sedimentary cycle (Upper Carboniferous – Permian) followed ...
Eugenio Trumpy +2 more
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Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification [PDF]
, 2013 The Maximum Likelihood (ML) and Cross Validation (CV) methods for estimating covariance hyper-parameters are compared, in the context of Kriging with a misspecified covariance structure. A two-step approach is used. First, the case of the estimation of a
Bachoc, François
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Bootstrap based uncertainty bands for prediction in functional kriging [PDF]
, 2016 The increasing interest in spatially correlated functional data has led to the development of appropriate geostatistical techniques that allow to predict a curve at an unmonitored location using a functional kriging with external drift model that takes ...
Franco-Villoria, Maria +1 more
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Journal of Geodesy, 2020 The study intercompares three stochastic interpolation methods originating from the same geostatistical family: least-squares collocation (LSC) known from geodesy, as well as ordinary kriging (OKR) and universal kriging (UKR) known from geology and other
W. Jarmołowski +3 more
semanticscholar +1 more source