A Class-Kriging predictor for functional compositions with application to particle-size curves in heterogeneous aquifers

DOI10.1007/s11004-015-9625-7zbMath1397.86005OpenAlexW2284033163MaRDI QIDQ1789200

Alberto Guadagnini, Piercesare Secchi, Alessandra Menafoglio

Publication date: 10 October 2018

Published in: Mathematical Geosciences (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/11311/977846

zbMATH Keywords

clusteringgroundwaterhydrogeologyparticle-size curves

Mathematics Subject Classification ID

Hydrology, hydrography, oceanography (86A05) Geostatistics (86A32)

Related Items (7)

Compositional regression with functional response ⋮ Orthogonal decomposition of multivariate densities in Bayes spaces and relation with their copula-based representation ⋮ Bivariate densities in Bayes spaces: orthogonal decomposition and spline representation ⋮ Additive Functional Regression for Densities as Responses ⋮ Unnamed Item ⋮ Statistical analysis of complex and spatially dependent data: a review of object oriented spatial statistics ⋮ Compositional scalar-on-function regression with application to sediment particle size distributions

Uses Software

• fda (R)

Cites Work

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• Bayes Hilbert Spaces
• Overview of object oriented data analysis
• Object Oriented Data Analysis: A few methodological challenges
• Geometric approach to statistical analysis on the simplex
• Kriging prediction for manifold-valued random fields

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