A random matrix theory pipeline using Hilbert space-filling curves and Bergsma correlation isolates core spatial dependence in spatial time series by removing strong temporal signals, applied to Indian temperature data to reveal topography- and urbanization-driven anomalies.
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Eliciting core spatial association from spatial time series: a random matrix approach
A random matrix theory pipeline using Hilbert space-filling curves and Bergsma correlation isolates core spatial dependence in spatial time series by removing strong temporal signals, applied to Indian temperature data to reveal topography- and urbanization-driven anomalies.