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stat.ME2025
Calibrated Bayesian inference for random fields on large irregular domains using the debiased spatial Whittle likelihood
Thomas Goodwin, Arthur Guillaumin, Matias Quiroz +2
Bayesian inference for stationary random fields is computationally demanding. Whittle-type likelihoods in the frequency domain based on the fast Fourier Transform (FFT) have severa…
stat.ME2025
A Beta Cauchy-Cauchy (BECCA) shrinkage prior for Bayesian variable selection
Linduni M. Rodrigo, Robert Kohn, Hadi M. Afshar +1
This paper introduces a novel Bayesian approach for variable selection in high-dimensional and potentially sparse regression settings. Our method replaces the indicator variables i…
stat.ME2024
Spectral domain likelihoods for Bayesian inference in time-varying parameter models
Oskar Gustafsson, Mattias Villani, Robert Kohn
Inference for locally stationary processes is often based on some local Whittle-type approximation of the likelihood function defined in the frequency domain. The main reasons for…