19972020

Research output per year

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Personal profile

Biography

Gael Martin is a Professor of Econometrics in the Department of Econometrics and Business Statistics. Her primary research interests are:

Bayesian Inference; Computational Statistics; Probabilistic Forecasting; Financial Econometrics; Time Series Analysis; Long Memory Time Series; Count Time Series

An up-to-date list of publications, work in progress, ARC grant projects, and editorial, supervision and teaching responsibilities can be found at the following personal home page web address:

http://www-personal.buseco.monash.edu.au/~gmartin/

This personal home page is regularly maintained.

(The Faculty profile page is often out-of-date.)

 

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Projects

Research Output

High-frequency jump tests: which test should we use?

Maneesoonthorn, W., Martin, G. M. & Forbes, C. S., 2020, (Accepted/In press) In : Journal of Econometrics. 10 p.

Research output: Contribution to journalArticleResearchpeer-review

Issues in the estimation of mis-specified models of fractionally integrated processes

Martin, G. M., Nadarajah, K. & Poskitt, D. S., Apr 2020, In : Journal of Econometrics. 215, 2, p. 559-573 15 p.

Research output: Contribution to journalArticleResearchpeer-review

Approximate Bayesian forecasting

Frazier, D. T., Maneesoonthorn, W., Martin, G. M. & McCabe, B. P. M., 1 Apr 2019, In : International Journal of Forecasting. 35, 2, p. 521-539 19 p.

Research output: Contribution to journalArticleResearchpeer-review

3 Citations (Scopus)

Auxiliary likelihood-based approximate Bayesian computation in state space models

Martin, G. M., McCabe, B. P. M., Frazier, D. T., Maneesoonthorn, W. & Robert, C. P., 2019, In : Journal of Computational and Graphical Statistics. 28, 3, p. 508-522 15 p.

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Construction and visualization of confidence sets for frequentist distributional forecasts

Harris, D., Martin, G. M., Perera, I. & Poskitt, D. S., 2019, In : Journal of Computational and Graphical Statistics. 28, 1, p. 92-104 13 p.

Research output: Contribution to journalArticleResearchpeer-review