Associate Professor Janice Scealy

Janice Scealy

RSFAS

Research School of Finance, Actuarial Studies & Statistics

Position
Associate Professor
Email
janice.scealy@anu.edu.au
Phone number
+61 2 612 57295
Office
Room 4.22, CBE Bld (26C)
Research areas

Statistics; Statistical theory; Applied statistics.

Biography

Janice Scealy is a research Statistician specialising in the analysis of complex structured datasets. Janice's research interests include:  compositional data analysis; directional statistics; shape analysis and statistics for manifold-valued data; robust statistics; statistics in the Earth Sciences; applications in palaeomagnetism, seismology and geochemistry; geostatistics and the analysis of spatial data; and model selection in linear mixed models. Janice’s research appears in leading academic journals including Journal of the American Statistical AssociationJournal of the Royal Statistical Society Series BStatistical Science, Statistics and Computing, International Statistical Review, Australian and New Zealand Journal of Statistics, TEST, Journal of Geophysical Research: Solid Earth and Geophysical Journal International. Janice was awarded the Moran Medal in 2021 by the Australian Academy of Science. Janice has also achieved previous major grant success which includes two Discovery Projects (one in the Mathematical Sciences and one in the Earth Sciences), and a Discovery Early Career Researcher Award. Janice is listed as one of 60 historical and prominent Australian Statisticians (Significance Magazine).

 

Research publications

Refereed Journal Articles

Scealy, J. L., Hingee, K. L., Kent, J. T. and Wood, A. T. A. (2024). Robust score matching for compositional data, Statistics and Computing, acepted on 17/02/24.

Hoggard, M. J., Scealy, J. L. and Delbridge, B. G. (2024). Seismic moment tensor classification using elliptical distribution functions on the hypersphere, Geophysical Journal International, 237.

Heslop, D., Scealy, J. L., Wood, A. T. A., Roberts, A. P. and Tauxe, L. (2023). A bootstrap common mean direction test, Journal of Geophysical Research: Solid Earth, 128, 8. 

Scealy, J. L. and Wood, A. T. A. (2023). Score matching for compositional distributions. Journal of the American Statistical Association, 118, 1811-1823.

Scealy, J. L., Heslop, D., Liu, J. and Wood, A. T. A. (2021). Directions old and new: paleomagnetism and Fisher (1953) meet modern statistics, International Statistical Review, 90, 237-258.

Scealy, J. L. (2021). Comments on: Recent advances in directional statistics. TEST, 30, 68-70.

Scealy, J. L. and Wood, A. T. A. (2021). Analogues on the sphere of the affine-equivariant spatial median. Journal of the American Statistical Association, 116, 1457-1471.

Scealy, J. L. and Wood, A. T. A. (2019). Scaled von Mises-Fisher distributions and regression models for paleomagnetic directional data. Journal of the American Statistical Association, 114, 1547-1560.

Scealy, J. L. and Welsh, A. H. (2017). A Directional mixed effects model for compositional expenditure data. Journal of the American Statistical Association, 112, 24-36.

Scealy, J. L., Caritat, P. de, Grunsky, E. C., Tsagris, M. T. and Welsh, A. H. (2015). Robust principal component analysis for power transformed compositional data. Journal of the American Statistical Association, 110, 136-148. 

Scealy, J. L. and Welsh, A. H. (2014). Fitting Kent models to compositional data with small concentration. Statistics and Computing, 24, 165-197.

Scealy, J. L. and Welsh, A. H. (2014). Colours and cocktails: compositional data analysis 2013 Lancaster Lecture. Australian & New Zealand Journal of Statistics, 56, 145-169.

Mueller, S., Scealy, J. L. and Welsh, A. H. (2013). Model selection in linear mixed models. Statistical Science, 28, 135-167.

Scealy, J. L. and Welsh, A. H. (2011). Regression for compositional data by using distributions defined on the hypersphere. Journal of the Royal Statistical Society Series B, 73, 351-375.

Other research outputs 

Scealy, J. L. (2010). Small area estimation using a multinomial logit mixed model with category specific random effects. ABS Research paper, catalogue number 1351.0.55.029.

Wooton, J. L. (2007). Measuring and correcting for information loss in confidentialised census counts. ABS Methodology Advisory Committee research paper, catalogue number 1352.0.55.083. (Note: prior to 2008 Janice published the name Wooton).

Wooton, J. L. and Fraser, B. (2005). A review of confidentiality protections for statistical tables. ABS Methodology Advisory Committee research paper, catalogue number 1352.0.55.072.

Research grants and awards

2021 Moran Medal, Australian Academy of Science.

 

Mathematical Science ARC Discovery Project

DP220102232: Novel statistical methods for data with non-Euclidean geometric structure.

 

Earth Science ARC Discovery Project

DP190100874: A new generation of palaeomagnetic statistics.

 

ARC Discovery Early Career Researcher Award

DE180100220: Statistics for manifold-valued data.

 

 

Research engagement and outreach

Research

https://cosmosmagazine.com/earth/earthquake-or-nuclear-bomb-telling-the-difference-just-got-easier/ 

https://ras.ac.uk/news-and-press/news/end-nuclear-secrecy-underground-tests-now-99-detectable

https://reporter.anu.edu.au/all-stories/new-method-to-more-accurately-spot-underground-nuclear-tests

https://www.earth.com/news/underground-nuclear-testing-will-no-longer-be-a-secret-thanks-to-new-technology/

https://phys.org/news/2024-02-australian-method-accurately-underground-nuclear.html?deviceType=desktop

https://theconversation.com/underground-nuclear-tests-are-hard-to-detect-a-new-method-can-spot-them-99-of-the-time-222500

https://medriva.com/breaking-news/unveiling-the-underground-a-revolutionary-method-for-detecting-secret-nuclear-tests/

https://interestingengineering.com/science/method-spots-underground-nuclear-tests-accurately

https://www.menastar.com/news/national/article_54ff3253-9c60-5103-b563-ffb7528ac58c.html

https://www.miragenews.com/new-method-detects-underground-nuclear-tests-99-1169677/

https://www.nationaltribune.com.au/underground-nuclear-tests-are-hard-to-detect-a-new-method-can-spot-them-99-of-the-time/

 

Career 

https://cosmosmagazine.com/science/mathematics/statistics-janice-scealy/

https://amsi.org.au/2021/03/18/mathematical-sciences-leaders-honoured-by-australian-academy-of-science/

https://cbe.anu.edu.au/news/2021/anu-academic-wins-prominent-australian-research-award

https://vimeo.com/508228144

https://www.miragenews.com/shining-stars-of-science-honoured-with-academy-526524/

 

Teaching

Current Teaching: 

STAT7039 Principles of Mathematical Statistics