Bertolacci, Michael G.

Selected Publications

• Journal Article

  Year	Title
  2022	AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series Published In Journal of Computational and Graphical Statistics
  2022	From Many to One: Consensus Inference in a MIP Published In GEOPHYSICAL RESEARCH LETTERS
  2022	WOMBAT v1.0: A fully Bayesian global flux-inversion framework Published In Geoscientific Model Development
  2020	Climate inference on daily rainfall across the Australian continent, 1876¿2015 Published In Annals of Applied Statistics
  2019	Climate inference on daily rainfall across the Australian continent, 1876¿2015 Published In Annals of Applied Statistics

• Conference Paper

  Year	Title
  2007	Are approximation algorithms for consensus clustering worthwhile? Published In Proceedings of the 7th SIAM International Conference on Data Mining
  2006	New algorithms research for first year students Published In Working Group Reports on ITiCSE on Innovation and Technology in Computer Science Education 2006
  2006	New algorithms research for first year students Published In ITiCSE06 - Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education

Investigator On

Year	Title
2021 - 2022	Spatio-Temporal Statistical Methods for Producing OCO-2/OCO-3 Level 3 and Level 4 Estimates Awarded by: NASA Funding Scheme: Research Opportunities in Space and Earth Sciences (ROSES)

Position Title

Preferred Title

Primary Email

• michael_bertolacci@uow.edu.au

Phone

• +612 4239 2388

Research Areas

• 0104 - STATISTICS

Research Overview

• I am interested in large scale spatio-temporal problems in environmental statistics. My previous research involved developing hierarchical Bayesian mixture models for the analysis of Australian daily rainfall at the continental scale. I also investigated methods for modelling multiple nonstationary time series in the spectral domain, as applied to spatial datasets including monthly rainfall and measles epidemiology.

  My current research focuses on spatio-temporal flux inversion for trace gases using remotely sensed data.

Selected Publications

• Journal Article

  Year	Title
  2022	AdaptSPEC-X: Covariate-Dependent Spectral Modeling of Multiple Nonstationary Time Series Published In Journal of Computational and Graphical Statistics
  2022	From Many to One: Consensus Inference in a MIP Published In GEOPHYSICAL RESEARCH LETTERS
  2022	WOMBAT v1.0: A fully Bayesian global flux-inversion framework Published In Geoscientific Model Development
  2020	Climate inference on daily rainfall across the Australian continent, 1876¿2015 Published In Annals of Applied Statistics
  2019	Climate inference on daily rainfall across the Australian continent, 1876¿2015 Published In Annals of Applied Statistics

• Conference Paper

  Year	Title
  2007	Are approximation algorithms for consensus clustering worthwhile? Published In Proceedings of the 7th SIAM International Conference on Data Mining
  2006	New algorithms research for first year students Published In Working Group Reports on ITiCSE on Innovation and Technology in Computer Science Education 2006
  2006	New algorithms research for first year students Published In ITiCSE06 - Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education

Investigator On

Year	Title
2021 - 2022	Spatio-Temporal Statistical Methods for Producing OCO-2/OCO-3 Level 3 and Level 4 Estimates Awarded by: NASA Funding Scheme: Research Opportunities in Space and Earth Sciences (ROSES)

Position Title

Preferred Title

Primary Email

• michael_bertolacci@uow.edu.au

Phone

• +612 4239 2388