Econometrics Seminar - Matias Quiroz (UTS)
Title: Spectral subsampling MCMC for stationary time series models
Abstract: Bayesian inference via Markov Chain Monte Carlo (MCMC) using subsampling methods for large datasets on large datasets has developed rapidly in recent years. However, the underlying methods are generally limited to relatively simple settings where the data have specific forms of independence. We propose a novel technique for speeding up MCMC for time series data by efficient data subsampling in the frequency domain. For several challenging time series models, our method demonstrates a speedup of up to two orders of magnitude while incurring negligible bias compared to MCMC on the full dataset.