Song's Reseach Interests

My research is motivated by modern applied problems arising from complex surveys, social/sensor networks, big data, and environmental science, and goes deep in statistical theory. In particular, my current interests include:

Nonparametric and semiparametric methods: empirical likelihood, density ratio modeling, bootstrap, etc.
Sample surveys: analysis for complex surveys with missing data, small area esimation
Statistical computing with big data
Network analysis, monitoring-sensor data analysis
Spatial-temporal modeling

Song Cai

Associate Professor

PhD in Statistics, UBC, 2014

MSc in Atmospheric Science, UBC, 2008

Office: 5215 Herzberg Laboratories

Email: scai@math.carleton.ca

Phone: 613-520-2600 x 2423

Cai, S., Qin, Y., Rao, J.N.K., Winiszewska, M. (2019). Empirical likelihood confidence intervals under imputation for missing survey data from stratified simple random sampling. The Canadian Journal of Statistics, 47(2), 281–301.

Cai, S. and Chen, J. (2018). Empirical likelihood inference for multiple censored samples. The Canadian Journal of Statistics, 46(2), 212–232.

Cai, S., Chen, J., and Zidek, J. V. (2017). Hypothesis testing in the presence of multiple samples under density ratio models. Statistica Sinica, 27(2), 761–783.

Cai, S., Chen, J. (2016). Empirical likelihood inference under density ratio models based on Type I censored samples: hypothesis testing and quantile estimation. In Advanced Statistical Methods in Data Science, 123–151, Springer, New York.

Cai, S., Zidek, J. V., Newlands, N., and Neilsen, D. (2014). Statistical modeling and forecasting of fruit crop phenology under climate change. Environmetrics, 25(8), 621–629.

Song's Reseach Interests

Song Cai

Selected Publications

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