Pages that link to "Item:Q367212"

The following pages link to A universal kriging predictor for spatially dependent functional data of a Hilbert space (Q367212):

Displaying 32 items.

• Simplicial principal component analysis for density functions in Bayes spaces (Q121360) (← links)
• Kriging for Hilbert-space valued random fields: the operatorial point of view (Q268732) (← links)
• Optimal sampling designs for nonparametric estimation of spatial averages of random fields (Q268787) (← links)
• Best estimation of functional linear models (Q311804) (← links)
• A universal kriging predictor for spatially dependent functional data of a Hilbert space (Q367212) (← links)
• Recent developments in complex and spatially correlated functional data (Q783297) (← links)
• Statistical issues in radiosonde observation of atmospheric temperature and humidity profiles (Q1642395) (← links)
• Statistical modeling of spatial big data: an approach from a functional data analysis perspective (Q1642410) (← links)
• Modeling spatially dependent functional data via regression with differential regularization (Q1733289) (← links)
• Statistical analysis of complex and spatially dependent data: a review of object oriented spatial statistics (Q1751652) (← links)
• A Class-Kriging predictor for functional compositions with application to particle-size curves in heterogeneous aquifers (Q1789200) (← links)
• Estimation of the mean for spatially dependent data belonging to a Riemannian manifold (Q1950885) (← links)
• Spatial prediction and spatial dependence monitoring on georeferenced data streams (Q1985963) (← links)
• Fast geostatistical seismic inversion coupling machine learning and Fourier decomposition (Q2009850) (← links)
• Machine learning of multiscale active force generation models for the efficient simulation of cardiac electromechanics (Q2020283) (← links)
• Inference for spatial regression models with functional response using a permutational approach (Q2078566) (← links)
• Machine learning for fast and reliable solution of time-dependent differential equations (Q2222523) (← links)
• Compositional data: the sample space and its structure (Q2273168) (← links)
• A functional data analysis approach to surrogate modeling in reservoir and geomechanics uncertainty quantification (Q2399815) (← links)
• Object oriented data analysis: a few methodological challenges (Q2922181) (← links)
• O2S2 for the Geodata Deluge (Q3300645) (← links)
• Efficient State/Parameter Estimation in Nonlinear Unsteady PDEs by a Reduced Basis Ensemble Kalman Filter (Q4636410) (← links)
• (Q4669764) (← links)
• Kriging Riemannian Data via Random Domain Decompositions (Q5066456) (← links)
• Functional regression models: Some directions of future research (Q5142169) (← links)
• Kriging prediction for manifold-valued random fields (Q5964278) (← links)
• Modeling geospatial uncertainty of geometallurgical variables with Bayesian models and Hilbert-kriging (Q6084314) (← links)
• Nonparametric Prediction for Spatial Dependent Functional Data Under Fixed Sampling Design (Q6107047) (← links)
• Trend filtering for functional data (Q6548836) (← links)
• Grassmannian kriging with applications in POD-based model order reduction (Q6584836) (← links)
• Unified Principal Component Analysis for Sparse and Dense Functional Data under Spatial Dependency (Q6620973) (← links)
• A permutation approach to the analysis of spatiotemporal geochemical data in the presence of heteroscedasticity (Q6626154) (← links)