Lower-bounds on the Bayesian Risk in estimation procedures via Sibson's alpha-Mutual Information

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Cardiocirculatory mathematical models are valuable tools for investigating both physiological and pathological conditions of the circulatory system. To assess an individual's clinical condition, these models must be tailored through parameter calibration. ...

The problem of covariance estimation for replicated surface-valued processes is examined from the functional data analysis perspective. Considerations of statistical and computational efficiency often compel the use of separability of the covariance, even ...

Diffusion adaptation is a powerful strategy for distributed estimation and learning over networks. Motivated by the concept of combining adaptive filters, this work proposes a combination framework that aggregates the operation of multiple diffusion strate ...

Motivated by the widespread use of large gridded data sets in the atmospheric sciences, we propose a new model for extremes of areal data that is inspired by the simultaneous autoregressive (SAR) model in classical spatial statistics. Our extreme SAR model ...

We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We show that the optimal estimator and the least favorable distribution form a Nash equilibrium. Despit ...

The estimation of the apparent axon diameter (AAD) via diffusion MRI is affected by the incoherent alignment of single axons around its axon bundle direction, also known as orientational dispersion. The simultaneous estimation of AAD and dispersion is chal ...

This contribution seeks to identify a few factors that have contributed to the success of a thriving discipline, and to identify threats that could put future prospects at risk. Many of these factors are not specific to magnetic resonance, and may also app ...

Max-stable processes are the natural analogues of the generalized extreme-value distribution when modelling extreme events in space and time. Under suitable conditions, these processes are asymptotically justified models for maxima of independent replicati ...

We describe a prototype approach to flexible modelling for maxima observed at sites in a spatial domain, based on fitting of max-stable processes derived from underlying Gaussian random fields. The models we propose have generalised extreme-value marginal ...

Lower-bounds on the Bayesian Risk in estimation procedures via Sibson's alpha-Mutual Information

Chattez avec Graph Search

Two New Calibration Techniques of Lumped-Parameter Mathematical Models for the Cardiovascular System

Random Surface Covariance Estimation by Shifted Partial Tracing

Affine Combination of Diffusion Strategies Over Networks

Simultaneous autoregressive models for spatial extremes

Wasserstein Distributionally Robust Kalman Filtering

Orientation-Dispersed Apparent Axon Diameter via Multi-Stage Spherical Mean Optimization

A bright future for magnetic resonance

Space-time modelling of extreme events

Geostatistics of extremes