Research in the Department of Statistics and Actuarial Science at SFU encompasses many areas of statistical methodology, actuarial science and finance. The Department prides itself on a strong tradition of inter-disciplinary work. The following is a summary of our research interests and activities. Please see the individual faculty webpages for further details.

Inter-disciplinary Research

Research areas of application include agriculture (Loughin), ecology (Cao, Loughin, Routledge,  Schwarz), engineering (Loughin), environmental science (Cao, Thompson), genomics and genetics (Cao, Graham, McNeney), industry and manufacturing (Bingham, Loughin, Tang, Thompson), insurance and finance (Bégin, Lu, Parker, Sanders, Tsai), medicine (Altman, Cao, Graham, Hu, Loughin, McNeney, Thompson), pension plans (Parker, Sanders), physics (Bingham, Lockhart), sport (Loughin, Swartz), financial enginerring (Bégin), economics (Bégin).

Actuarial Science and Finance

Research areas in actuarial science and finance include risk theory (Lu, Tsai), stochastic modeling (Bégin, Lu, Tsai), longevity risk (Tsai), pension plans (Parker, Sanders), risk management in insurance and finance (Bégin, Lu, Parker, Sanders, Tsai), financial econometrics (Bégin), credit risk (Bégin), option pricing theroy (Bégin).

Statistical  Methodology

Research on statistical methodology in the Department includes longitudinal and correlated data methods (Altman, Hu), categorical data methods (Altman, Loughin), Bayesian methods (Bingham, Cao, Graham, Swartz, Wang), design of experiments  (Bingham, Loughin, Tang, Thompson), functional data analysis methods (Campbell, Cao, Wang), estimating dynamical models (Campbell, Cao), statistical computing and Monte Carlo methods (Cao, Graham, McNeney, Swartz, Wang), goodness-of-fit testing (Lockhart, Stephens), stochastic process modeling (Altman, Bégin, Graham, Lockhart, Lu, Sanders, Tsai), statistical learning/data mining (Loughin), population size estimation methods (Routledge, Schwarz, Thompson), sampling theory (Thompson).

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