David Frazier
David Frazier
Monash University, Department of Econometrics and Business Statistics
Verified email at monash.edu - Homepage
TitleCited byYear
Asymptotic properties of approximate Bayesian computation
DT Frazier, GM Martin, CP Robert, J Rousseau
Biometrika 105 (3), 593-607, 2018
Model misspecification in abc: Consequences and diagnostics
DT Frazier, CP Robert, J Rousseau
arXiv preprint arXiv:1708.01974, 2017
Approximate bayesian forecasting
DT Frazier, W Maneesoonthorn, GM Martin, BPM McCabe
International Journal of Forecasting 35 (2), 521-539, 2019
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
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
Indirect inference with a non-smooth criterion function
DT Frazier, T Oka, D Zhu
Journal of Econometrics 212 (2), 623-645, 2019
Efficient two-step estimation via targeting
DT Frazier, E Renault
Journal of econometrics 201 (2), 212-227, 2017
Indirect inference with (out) constraints
DT Frazier, E Renault
arXiv preprint arXiv:1607.06163, 2016
Indirect Inference with Endogenously Missing Exogenous Variables
S Chaudhuri, DT Frazier, E Renault
Forthcoming: Journal of Econometrics, 2016
Robust Approximate Bayesian Inference with Synthetic Likelihood
DT Frazier, C Drovandi
arXiv preprint arXiv:1904.04551, 2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments
DJ Nott, C Drovandi, R Kohn
arXiv preprint arXiv:1902.04827, 2019
Indirect inference: which moments to match?
DT Frazier, E Renault
Econometrics 7 (1), 14, 2019
Indirect Inference for Locally Stationary Models
D Frazier, B Koo
Available at SSRN 3192792, 2018
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Articles 1–13