Teaching

In 2015 - 2016, I teach ST444: Statistical Computing (master level, both lectures and seminars) and ST301: Actuarial Mathematics (Life) (undergraduate level, seminars only). Course materials can be found via Moodle.

Last year, I lectured Part III course Time Series at Cambridge. More information can be found here. 

Research

My current research interests include shape-constrained estimation, time series analysis, change-point detection and statistical computing. Here is a list of my publications and preprints:

Core Statistical Publications:

• Chen, Y. and Samworth, R. J. (2016+), Generalised additive and index models with shape constraints, Journal of Royal Statistical Society, Series B, to appear. (.pdf) The accompanying R package scar, short for shape constrained additive regression, is available from CRAN.
   
• Chen, Y. and Wellner, J. A. (2016), On convex least squares estimation when the truth is linear, Electronic Journal of Statistics, 10, 171-209. (.pdf)
   
• Chen, Y. (2015), Semiparametric time series models with log-concave innovations: maximum likelihood estimation and its consistency, Scandinavian Journal of Statistics, 42, 1-31. (.pdf)

• Chen, Y. and Samworth, R. J. (2013), Smoothed log-concave maximum likelihood estimation with applications, Statistica Sinica, 23, 1373-1398. (.pdf)

Statistical Software:

• Chen, Y. and Samworth, R. J. (2014), SCAR, An R package for shape constrained additive regression, version 0.2-1 available from available from CRAN.

• Cule, M. L., Gramacy, R. B., Samworth, R. J. and Chen, Y. (2007), LogConcDEAD, An R package for log-concave density estimation in arbitrary dimensions, version 1.5-4 available from CRAN.

Invited Discussion:

• Chen, Y., Shah, R. D. and Samworth, R. J. (2014) Discussion of Multiscale change point inference by Frick, Munk and Sieling, Journal of Royal Statistical Society: Series B, 76, 544-546.   

• Chen, Y. (2012), Discussion of Constructing summary statistics for approximate bayesian computation: semi-automatic ABC by Fearnhead and Prangle, Journal of the Royal Statistical Society: Series B, 74, 455.

• Chen, Y. (2010), Discussion of Maximum likelihood estimation of a multidimensional log-concave density by Cule, Samworth and Stewart, Journal of the Royal Statistical Society: Series B, 72, 590-593.

Interdisciplinary Publications:

• Kosmoliaptsis, V., Mallon, D. H., Chen, Y., Bolton, E. M.,  Bradley, J. A. and Taylor, C. J. (2016+) Alloantibody responses after renal transplant failure can be better predicted by donor–recipient HLA amino acid sequence and physicochemical disparities than conventional HLA matching, American Journal of Transplantation, to appear.

• Hamed, M. O., Chen, Y., Pasea, L., Watson, C. J., Torpey, N., Bradley, A., Pettigrew, G. J. and Saeb-Parsy, K. (2015) Early graft loss after kidney transplantation: risk factors and consequences, American Journal of Transplantation, 15, 1632-1643.

• Kosmoliaptsis, V., Salji, M., Bardsley, V., Chen, Y., Thiru, S., Griffiths, M. H., Copley, H. C., Saeb-Parsy, K., Bradley, A., Torpey, N. and Pettigrew, G. J. (2014) Baseline donor chronic renal injury confers the same transplant survival disadvantage for DCD and DBD kidneys, American Journal of Transplantation, 15, 754-763.

• Ali, J. M., Davies, S. E., Brais, R. J., Randle, L. V., Klinck, J. R., Allison, M. E. D., Chen, Y., Pasea, L., Harper, S. F. J. and Pettigrew, G. J. (2015) Analysis of ischaemia/reperfusion injury in time-zero biopsies predicts liver allograft outcomes, Liver Transplantation, 21, 487-499.