David Tyler Frazier
David Tyler Frazier
Monash University, Department of Econometrics and Business Statistics
Verified email at - Homepage
Cited by
Cited by
Forecasting: theory and practice
F Petropoulos, D Apiletti, V Assimakopoulos, MZ Babai, DK Barrow, ...
International Journal of Forecasting 38 (3), 705-871, 2022
Asymptotic properties of approximate Bayesian computation
DT Frazier, GM Martin, CP Robert, J Rousseau
Biometrika 105 (3), 593-607, 2018
Model misspecification in approximate Bayesian computation: consequences and diagnostics
DT Frazier, CP Robert, J Rousseau
Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2020
Auxiliary likelihood-based approximate Bayesian computation in state space models
GM Martin, BPM McCabe, DT Frazier, W Maneesoonthorn, CP Robert
Journal of Computational and Graphical Statistics 28 (3), 508-522, 2019
Robust approximate Bayesian inference with synthetic likelihood
DT Frazier, C Drovandi
Journal of Computational and Graphical Statistics 30 (4), 958-976, 2021
Approximate bayesian forecasting
DT Frazier, W Maneesoonthorn, GM Martin, BPM McCabe
International Journal of Forecasting 35 (2), 521-539, 2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments
DT Frazier, DJ Nott, C Drovandi, R Kohn
arXiv preprint arXiv:1902.04827, 2019
Focused Bayesian prediction
R Loaiza‐Maya, GM Martin, DT Frazier
Journal of Applied Econometrics 36 (5), 517-543, 2021
Computing Bayes: Bayesian computation from 1763 to the 21st century
GM Martin, DT Frazier, CP Robert
arXiv preprint arXiv:2004.06425, 2020
A comparison of likelihood-free methods with and without summary statistics
C Drovandi, DT Frazier
Statistics and Computing 32 (3), 42, 2022
A new approach to risk-return trade-off dynamics via decomposition
DT Frazier, X Liu
Journal of Economic Dynamics and Control 62, 43-55, 2016
Efficient Bayesian synthetic likelihood with whitening transformations
JW Priddle, SA Sisson, DT Frazier, I Turner, C Drovandi
Journal of Computational and Graphical Statistics 31 (1), 50-63, 2022
Loss-based variational Bayes prediction
DT Frazier, R Loaiza-Maya, GM Martin, B Koo
Journal of Computational and Graphical Statistics, 1-31, 2024
Optimal probabilistic forecasts: When do they work?
GM Martin, R Loaiza-Maya, W Maneesoonthorn, DT Frazier, ...
International Journal of Forecasting 38 (1), 384-406, 2022
Synthetic likelihood in misspecified models: Consequences and corrections
DT Frazier, C Drovandi, DJ Nott
arXiv preprint arXiv:2104.03436, 2021
Robust and efficient approximate Bayesian computation: A minimum distance approach
DT Frazier
arXiv preprint arXiv:2006.14126, 2020
Efficient two-step estimation via targeting
DT Frazier, E Renault
Journal of Econometrics 201 (2), 212-227, 2017
Computing Bayes: From Then ‘Til Now
CPR Gael M. Martin, David T. Frazier
Statistical Science 1 (39), 3-19, 2024
Variational Bayes in state space models: Inferential and predictive accuracy
DT Frazier, R Loaiza-Maya, GM Martin
Journal of Computational and Graphical Statistics 32 (3), 793-804, 2023
Approximating Bayes in the 21st century
GM Martin, DT Frazier, CP Robert
Statistical Science 39 (1), 20-45, 2024
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