Bivariate Extreme Statistics, Ii

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Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

Recent cosmic shear studies have shown that higher-order statistics (HOS) developed by independent teams now outperform standard two-point estimators in terms of statistical precision thanks to their sensitivity to the non-Gaussian features of large-scale ...

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We enable the estimation of the per-axon axial diffusivity from single encoding, strongly diffusion-weighted, pulsed gradient spin echo data. Additionally, we improve the estimation of the per-axon radial diffusivity compared to estimates based on spherica ...

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This paper presents the experimental validation of a linear recursive state estimation (SE) process for hybrid AC/DC microgrids proposed in the authors' previous work. The SE uses a unified and linear measurement model that relies on the use of synchronize ...

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In the field of choice modeling, the availability of ever-larger datasets has the potential to significantly expand our understanding of human behavior, but this prospect is limited by the poor scalability of discrete choice models (DCMs): as sample sizes ...

Bivariate Extreme Statistics, Ii

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Timing and spatial selection bias in rapid extreme event attribution

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Networks with correlated edge processes

Axial and radial axonal diffusivities and radii from single encoding strongly diffusion-weighted MRI

Positive Definite Completions and Continuous Graphical Models

Bed Topography Inference from Velocity Field Using Deep Learning

Is There a Cap on Longevity? A Statistical Review

Machine Learning Security in Industry: A Quantitative Survey

Data-Driven Unknown-Input Observers and State Estimation

Statistical Emulation of Neural Simulators: Application to Neocortical L2/3 Large Basket Cells

Experimental Validation of a Unified and Linear State Estimation Method for Hybrid AC/DC Microgrids

Filtered data and eigenfunction estimators for statistical inference of multiscale and interacting diffusion processes

Stochastic adaptive resampling for the estimation of discrete choice models