Gunawan, David

Research Areas

0104 - STATISTICS

Research Overview

I have a general and broad interest in Bayesian computations, from both a methodological and an applied perspective. From a methodological perspective, I am interested in posterior simulation methods, such as Markov chain Monte Carlo, Sequential Monte Carlo, particle Markov chain Monte Carlo, Variational approximations, and Approximate Bayesian computation methods. From an applied perspective, I use Bayesian computational methods to solve real-world problems in many areas, such as economic inequality and poverty measurement, health, cognitive psychology, finance, economics, and environmental studies.

Geographic Focus

Wollongong Geographic Region

Available as Research Supervisor

Available for Collaborative Projects

Member Of

School of Mathematics and Applied Statistics

Selected Publications

Journal Article

Year	Title
2022	A Statistical Recurrent Stochastic Volatility Model for Stock Markets Published In Journal of Business and Economic Statistics
2022	Efficient Selection Between Hierarchical Cognitive Models: Cross-Validation With Variational Bayes Published In PSYCHOLOGICAL METHODS
2022	Inequality in Education: A Comparison of Australian Indigenous and Nonindigenous Populations Published In Statistics Politics and Policy
2021	Identifying relationships between cognitive processes across tasks, contexts, and time Published In Behavior Research Methods
2021	Posterior Probabilities for Lorenz and Stochastic Dominance of Australian Income Distributions* Published In Economic Record
2021	Variational Bayes approximation of factor stochastic volatility models Published In International Journal of Forecasting
2020	Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins Published In Statistics and Computing
2020	A flexible particle Markov chain Monte Carlo method Published In Statistics and Computing
2020	Bayesian assessment of Lorenz and stochastic dominance Published In Canadian Journal of Economics
2020	Bayesian weighted inference from surveys Published In Australian and New Zealand Journal of Statistics
2020	Efficient data augmentation for multivariate probit models with panel data: an application to general practitioner decision making about contraceptives Published In Journal of the Royal Statistical Society. Series C: Applied Statistics
2020	Mixed Marginal Copula Modeling Published In Journal of Business and Economic Statistics
2020	New estimation approaches for the hierarchical Linear Ballistic Accumulator model Published In Journal of Mathematical Psychology
2020	Robustly estimating the marginal likelihood for cognitive models via importance sampling Published In Behavior Research Methods
2020	Subsampling sequential Monte Carlo for static Bayesian models Published In Statistics and Computing
2019	Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins Published In Statistics and Computing
2018	Bayesian inference for health inequality and welfare using qualitative data Published In Economics Letters

Investigator On

Year	Title
2021 - 2024	ARC Research Hub for Transforming Energy Infrastructure Through Digital Engineering Awarded by: Australian Research Council (ARC) Funding Scheme: Industrial Transformation Research Hubs
2021	Bayesian Inference for Cognitive Models with Intractable Likelihood Awarded by: ACEMS (ARC Centre of Excellence for Mathematical & Statistical Frontiers) Funding Scheme: ACMES Sprint Scheme
2021	Bayesian inference for Evidence Accumullation Models with Intractable Likelihoods Awarded by: Australian Research Council (ARC) Funding Scheme: Discovery Projects

Available as Research Supervisor

Advisees

Graduate Advising Relationship

Degree	Research Title	Advisee
Doctor of Philosophy (Integrated)	Spatial statistical inference from a decision-theoretic viewpoint with application to non-Gaussian environmental data	Pearse, Alan
Doctor of Philosophy	Pricing American options under regime-switching model	Zheng, Yawen
Doctor of Philosophy	Modeling Climate Change Impacts on Crude Oil Prices	Hemasiri Nawarathna, Anjana Wijayawardhana

Keywords

Bayesian Estimation | Markov chain Monte Carlo | sequential Monte Carlo | variational Approximation | Approximate Bayesian Computation | Synthetic Likelihood | Hierarchical-statistical-models | Statistics | Intractable likelihood problems | Spatio-Temporal-Statistics | Time series analysis | big data

Full Name

David Gunawan

Mailing Address

39C Northfields Avenue

Wollongong

NSW

2522

Australia

Research Overview

I have a general and broad interest in Bayesian computations, from both a methodological and an applied perspective. From a methodological perspective, I am interested in posterior simulation methods, such as Markov chain Monte Carlo, Sequential Monte Carlo, particle Markov chain Monte Carlo, Variational approximations, and Approximate Bayesian computation methods. From an applied perspective, I use Bayesian computational methods to solve real-world problems in many areas, such as economic inequality and poverty measurement, health, cognitive psychology, finance, economics, and environmental studies.

Geographic Focus

Wollongong Geographic Region

Member Of

School of Mathematics and Applied Statistics

Selected Publications

Journal Article

Year	Title
2022	A Statistical Recurrent Stochastic Volatility Model for Stock Markets Published In Journal of Business and Economic Statistics
2022	Efficient Selection Between Hierarchical Cognitive Models: Cross-Validation With Variational Bayes Published In PSYCHOLOGICAL METHODS
2022	Inequality in Education: A Comparison of Australian Indigenous and Nonindigenous Populations Published In Statistics Politics and Policy
2021	Identifying relationships between cognitive processes across tasks, contexts, and time Published In Behavior Research Methods
2021	Posterior Probabilities for Lorenz and Stochastic Dominance of Australian Income Distributions* Published In Economic Record
2021	Variational Bayes approximation of factor stochastic volatility models Published In International Journal of Forecasting
2020	Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins Published In Statistics and Computing
2020	A flexible particle Markov chain Monte Carlo method Published In Statistics and Computing
2020	Bayesian assessment of Lorenz and stochastic dominance Published In Canadian Journal of Economics
2020	Bayesian weighted inference from surveys Published In Australian and New Zealand Journal of Statistics
2020	Efficient data augmentation for multivariate probit models with panel data: an application to general practitioner decision making about contraceptives Published In Journal of the Royal Statistical Society. Series C: Applied Statistics
2020	Mixed Marginal Copula Modeling Published In Journal of Business and Economic Statistics
2020	New estimation approaches for the hierarchical Linear Ballistic Accumulator model Published In Journal of Mathematical Psychology
2020	Robustly estimating the marginal likelihood for cognitive models via importance sampling Published In Behavior Research Methods
2020	Subsampling sequential Monte Carlo for static Bayesian models Published In Statistics and Computing
2019	Computationally efficient Bayesian estimation of high-dimensional Archimedean copulas with discrete and mixed margins Published In Statistics and Computing
2018	Bayesian inference for health inequality and welfare using qualitative data Published In Economics Letters

Investigator On

Year	Title
2021 - 2024	ARC Research Hub for Transforming Energy Infrastructure Through Digital Engineering Awarded by: Australian Research Council (ARC) Funding Scheme: Industrial Transformation Research Hubs
2021	Bayesian Inference for Cognitive Models with Intractable Likelihood Awarded by: ACEMS (ARC Centre of Excellence for Mathematical & Statistical Frontiers) Funding Scheme: ACMES Sprint Scheme
2021	Bayesian inference for Evidence Accumullation Models with Intractable Likelihoods Awarded by: Australian Research Council (ARC) Funding Scheme: Discovery Projects

Advisees

Graduate Advising Relationship

Degree	Research Title	Advisee
Doctor of Philosophy (Integrated)	Spatial statistical inference from a decision-theoretic viewpoint with application to non-Gaussian environmental data	Pearse, Alan
Doctor of Philosophy	Pricing American options under regime-switching model	Zheng, Yawen
Doctor of Philosophy	Modeling Climate Change Impacts on Crude Oil Prices	Hemasiri Nawarathna, Anjana Wijayawardhana

Keywords

Bayesian Estimation | Markov chain Monte Carlo | sequential Monte Carlo | variational Approximation | Approximate Bayesian Computation | Synthetic Likelihood | Hierarchical-statistical-models | Statistics | Intractable likelihood problems | Spatio-Temporal-Statistics | Time series analysis | big data

Full Name

David Gunawan

Mailing Address

39C Northfields Avenue

Wollongong

NSW

2522

Australia

Geographic Location

University of Wollongong

Orcid Id

http://orcid.org/0000-0002-0427-4311 (confirmed)

Scopus Id

16202726100

Overview

Research Areas

Research Overview

Geographic Focus

Available as Research Supervisor

Affiliation

Available for Collaborative Projects

Member Of

Publications

Selected Publications

Journal Article

Funding

Investigator On

Supervision

Available as Research Supervisor

Advisees

Graduate Advising Relationship

Background

Keywords

Contact

Full Name

Mailing Address

Geographic Location

Identity

Orcid Id

Scopus Id

Overview

Research Areas

Research Overview

Geographic Focus

Affiliation

Member Of

Publications

Selected Publications

Journal Article

Funding

Investigator On

Supervision

Advisees

Graduate Advising Relationship

Background

Keywords

Contact

Full Name

Mailing Address

Geographic Location

Identity

Orcid Id

Scopus Id

Visualisations

Research Areas

Geographic Focus