Projects per year
Personal profile
Biography
Personal Website: https://dtfrazier.netlify.com/
Research interests
Simulation-based inference in both the classical and Bayesian paradigm.
Financial Econometrics, with applications to asset pricing.
Nonparametric and semiparametric econometric modeling.
Monash teaching commitment
ETC 1010: Data Modeling and Computing
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Network
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Loss-based Bayesian Prediction
Martin, G., Frazier, D., Hyndman, R. & Maneesoonthorn, O.
19/06/20 → 18/06/23
Project: Research
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Consequences of Model Misspecification in Approximate Bayesian Computation
Australian Research Council (ARC)
1/02/20 → 1/02/24
Project: Research
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The Validation of Approximate Bayesian Computation: Theory and Practice
Martin, G., Frazier, D., Renault, E. & Robert, C.
Australian Research Council (ARC), Monash University, Brown University, Université Paris Dauphine (Paris Dauphine University)
1/02/17 → 31/12/21
Project: Research
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Modularized Bayesian analyses and cutting feedback in likelihood-free inference
Chakraborty, A., Nott, D. J., Drovandi, C. C., Frazier, D. T. & Sisson, S. A., 2023, In: Statistics and Computing. 33, 1, 17 p., 33.Research output: Contribution to journal › Article › Research › peer-review
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ABC of the future
Pesonen, H., Simola, U., Köhn-Luque, A., Vuollekoski, H., Lai, X., Frigessi, A., Kaski, S., Frazier, D. T., Maneesoonthorn, W., Martin, G. M. & Corander, J., 2022, (Accepted/In press) In: International Statistical Review. 26 p.Research output: Contribution to journal › Article › Research › peer-review
Open Access1 Citation (Scopus) -
A comparison of likelihood-free methods with and without summary statistics
Drovandi, C. & Frazier, D. T., Jun 2022, In: Statistics and Computing. 32, 3, 23 p., 42.Research output: Contribution to journal › Article › Research › peer-review
Open AccessFile3 Citations (Scopus) -
Approximate maximum likelihood for complex structural models
Czellar, V., Frazier, D. T. & Renault, E., Dec 2022, In: Journal of Econometrics. 231, 2, p. 432-456 25 p.Research output: Contribution to journal › Article › Research › peer-review
1 Citation (Scopus) -
Bayesian inference using synthetic likelihood: asymptotics and adjustments
Frazier, D. T., Nott, D. J., Drovandi, C. & Kohn, R., 2022, (Accepted/In press) In: Journal of the American Statistical Association. 12 p.Research output: Contribution to journal › Article › Research › peer-review
Open Access1 Citation (Scopus)