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stat.ME2026
Stabilised weighted data subsampling for accelerated inference in models with recursive likelihoods
Matias Quiroz, Aishwarya Bhaskaran, Zixuan Wang +1
Inference for models with recursively defined likelihoods is computationally demanding, limiting scalability to large datasets. We propose a stabilised weighted subsampling methodo…
stat.ME2026★ 2 cited
Dynamic linear regression models for forecasting time series with semi long memory errors
Thomas Goodwin, Matias Quiroz, Robert Kohn
Dynamic linear regression models forecast the values of a time series based on a linear combination of a set of exogenous time series while incorporating a time series process for…
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…