Mathematical Challenges in Measuring Variability Patterns for Precipitation Analysis

DOI10.1007/978-3-030-22044-0_3zbMath1436.86004OpenAlexW2987274569MaRDI QIDQ3296275

Maria Emelianenko, Viviana Maggioni

Publication date: 7 July 2020

Published in: Mathematics of Planet Earth (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-22044-0_3

zbMATH Keywords

data reductionergodicityisotropystationaritydecorrelationcentroidal Voronoi tessellationstatistical assumptionsprecipitation patternsempirical orthogonality functions

Mathematics Subject Classification ID

Geostatistics (86A32)

Uses Software

• NEVA

Cites Work

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• Fast Multilevel CVT-Based Adaptive Data Visualization Algorithm
• Centroidal Voronoi Tessellations: Applications and Algorithms
• Statistics for Spatial Data
• Centroidal Voronoi Tessellation-Based Reduced-Order Modeling of Complex Systems
• Convergence of the Lloyd Algorithm for Computing Centroidal Voronoi Tessellations
• On the condition number of covariance matrices in kriging, estimation, and simulation of random fields

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