Tootfinder

Calibrated Bayesian inference for random fields on large irregular domains using the debiased spatial Whittle likelihood
Thomas Goodwin, Arthur Guillaumin, Matias Quiroz, Mattias Villani, Robert Kohn
https://arxiv.org/abs/2505.23330

Calibrated Bayesian inference for random fields on large irregular domains using the debiased spatial Whittle likelihood
Bayesian inference for stationary random fields is computationally demanding. Whittle-type likelihoods in the frequency domain based on the fast Fourier Transform (FFT) have several appealing features: i) low computational complexity of only $\mathcal{O}(n \log n)$, where $n$ is the number of spatial locations, ii) robustness to assumptions of the data-generating process, iii) ability to handle missing data and irregularly spaced domains, and iv) flexibility in modelling the covariance function…

Grève Š Zaventem : la planète et les générations futures remercient les grévistes
https://bx1.be/communes/zaventem/laeroport-de-bruxelles-annule-mardi-au-moins-30-des-v…