Discovering optimally representative dynamical locations (ORDL) in big multivariate spatiotemporal data: a case study of precipitation in Australia from space to ground sensors

DOI10.1016/J.APM.2022.05.036zbMath1505.62498OpenAlexW4281570465MaRDI QIDQ2110042

Guoqi Qian, Benjamin Hines, Antoinette Tordesillas

Publication date: 21 December 2022

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2022.05.036

zbMATH Keywords

multivariate statisticstime series analysisstatistical depthempirical distribution theoryprecipitation analysis

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Directional data; spatial statistics (62H11) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Order statistics; empirical distribution functions (62G30)

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• Spatial modelling of linear regression coefficients for gauge measurements against satellite estimates
• Regression Quantiles
• Quantile functions for multivariate analysis: approaches and applications

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