Janice Scealy | Research School of Finance, Actuarial Studies and Statistics

Area of expertise:

Statistics

Research areas

Statistics; Statistical theory; Applied statistics.

Qualifications

PhD in Statistics, The Australian National University awarded on 01/2011. Thesis title: Modelling Techniques for Compositional Data Using Distributions Defined on the Hypersphere. Supervisor: Prof Alan Welsh.

Bachelor of Mathematics degree with first class honours in Statistics, University of Wollongong awarded on 12/2003.

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, geodynamics 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 Association, Journal of the Royal Statistical Society Series B, Statistical Science, Statistics and Computing, International Statistical Review, Journal of Multivariate Analysis, Australian and New Zealand Journal of Statistics, TEST, Journal of Geophysical Research: Solid Earth, Geophysical Journal International and Seismological Research Letters. 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), a Discovery Early Career Researcher Award and a Rio Tinto Centre for Future Materials grant. Janice is listed as one of 60 historical and prominent Australian Statisticians (Significance Magazine).

Grants

GEM-Cu: Geodynamic Environments for Mineralisation of Cu (Copper)
Davies, R. (PI), Goes, S. (CoI), Ham, D. (CoI), Hoggard, M. (CoI), Sambridge, M. (CoI), Scealy, J. (CoI), Shephard, G. (CoI), Steen, J. (CoI), Taylor, J. (CoI) & Walls-Nichols, E. (CoI)

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.

Publications

Refereed Journal Articles

Hoggard, M. J., Pasyanos, M. E., Scealy, J. L. and Delbridge, B. G. (2026). Seismic event characterisation using full moment tensors on the hypersphere. Seismological Research Letters, accepted on 25 March, 2026.

Hingee, K., Scealy, J. L. and Wood, A. T. A. (2025). Nonparametric bootstrap inference for the eigenvalues of geophysical tensors. Journal of the American Statistical Association, accepted on 17 November, 2025.

Xu, J., Scealy, J. L., Wood, A. T. A. and Zou, T. (2025). Generalized score matching. Journal of Multivariate Analysis, 210, 105473.

Scealy, J. L., Hingee, K. L., Kent, J. T. and Wood, A. T. A. (2024). Robust score matching for compositional data, Statistics and Computing, 34, article number 93.

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.