Le Chang

Le Chang


Research School of Finance, Actuarial Studies & Statistics

Phone number
+61 2 612 55116
Room 3.07, CBE Bld (26C)
Research areas

Model selection; Robust statistics; Spatial statistics; Graphical lasso; Mortality forecasting.


Le Chang is a Lecturer in Statistics.  His research relates to robust penalized regression and model averaging methods, with specific research foci including principal component analysis, clustering methods, spatio-temporal models, graphical lasso, mortality forecasting and other statistical applications to actuarial science. Le’s work has been published in highly-regarded outlets including TechnometricsInternational Journal of Forecasting, Scandinavian Actuarial Journal and ASTIN Bulletin.


Google Scholar

Research publications

Chang, L., Wang, J., and Woodgate. W, 2021. Analysing spectroscopy data using two-step group penalized partial least squares regression. Environmental and Ecological Statistics, to appear.

Chang, L. and Shi, Y., 2020. Mortality forecasting with a spatially penalized smoothed VAR model. ASTIN Bulletin: The Journal of the IAA, pp.1-29.

Jiang, X., Chang, L. and Shi, Y., 2020. A retrospective analysis of the dynamic transmission routes of the COVID-19 in mainland China. Scientific Reports, 10(1), pp.1-10.

Chang, L. and Shi, Y., 2020. Dynamic modelling and coherent forecasting of mortality rates: a time-varying coefficient spatial-temporal autoregressive approach. Scandinavian Actuarial Journal, pp.1-21.

Chang, L. and Shi, Y., 2020. Does Bitcoin dominate the price discovery of the Cryptocurrencies market? A time-varying information share analysis. Operations Research Letters, 48(5), pp.641-645.

Feng, L., Shi, Y. and Chang, L., 2020. Forecasting mortality with a hyperbolic spatial temporal VAR model. International Journal of Forecasting.

Wang, Q., Woodrow, I.E., Goodger, J.Q., Chang, L. and Elgar, M.A., 2019. Task-specific recognition signals are located on legs in a social insect. Frontiers in Ecology and Evolution7, p.227.

Chang, L., Roberts, S. and Welsh, AH., 2018. Robust Lasso Regression Using Tukey's Biweight Criterion. Technometrics, 60(1), pp.36-47.



Financial Mathematics (STAT2032/6046)

Principles of Mathematical Statistics (STAT 6039)



Principles of Mathematical Statistics (STAT 6039)

Survival Modelling (STAT3032/7042)

Financial Mathematics (STAT2032/6046)

Introduction to Bayesian Data Analysis (STAT3016)