2 papers
stat.CO2025
Variational inference for steady-state BVARs
Oskar Gustafsson, Mattias Villani
The steady-state Bayesian vector autoregression (BVAR) makes it possible to incorporate prior information about the long-run mean of the process. This has been shown in many studie…
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…