# Yining Chen

Statistical Laboratory,
Centre for Mathematical Sciences,

Y.Chen@statslab.cam.ac.uk
Room: D0.20
Office phone: +44 1223 339792

I am a postdoctoral research associate in statistics at the Statistical Laboratory, which is part of the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge. My supervisor is Prof. Richard Samworth. I help running the Cambridge Statistics Clinic fortnightly. Please feel free to email us if you are a member of the university and need statistical consulting services.

## Teaching

In Lent 2014-2015, I lecture Part III course Time Series. Here I maintain a course website.

I also supervise Part IB course Statistics. Previously, I have supervised Part II courses Principles of Statistics and Statistical Modelling, and have been Teaching Assistant of Part III course Applied Statistics.

## Research

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

• Chen, Y. and Wellner, J. A. (2014), On convex least squares estimation when the truth is linear, Preprint. (.pdf)
• Chen, Y. and Samworth, R. J. (2014), 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. (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)
• 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. (.pdf). Some associated R code can be found here.
• 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. (.pdf)
• 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.

• Chen, Y. (2013), Aspects of Shape-constrained Estimation in Statistics, PhD Thesis, University of Cambridge. (.pdf).
• Chen, Y. (2010), A comparison between different classification techniques, MPhil Thesis, University of Cambridge.

## Talks

Here is a list of talks I gave previously:

• Semiparametric time series models with log-concave innovations.
• Royal Statistical Society International Conference, Telford, UK, 2012
• 8th World Congress on Probability and Statistics, Istanbul, Turkey, 2012
• An introduction to shape-constrained estimation problems.
• Statistical Laboratory Graduate Seminar, Cambridge, U.K., 2012. Some notes on the talk can be found here.
• Smoothed log-concave maximum likelihood estimation with applications.
• IMS China International Conference on Statistics and Probability, Xi'an, China, 2011
• Research Students' Conference in Probability and Statistics, Cambridge, UK, 2011

Yining Chen, Last update: Jan 2015