Are you applying to universities? | SHARE YOUR EXPERIENCE Are you applying to universities? | SHARE YOUR EXPERIENCE

Bayesian Nonparametrics for Multiple Systems Estimation

   School of Mathematics

   Applications accepted all year round  Competition Funded PhD Project (UK Students Only)

About the Project

Estimating population size is a common problem in statistics with many well-established methods. However, these methods rely on strict assumptions about the structure of the population. These assumptions are often unrealistic and may result in faulty population estimates. Methodology to estimate population size is commonly applied to epidemic and ecological data sets, but is being increasingly applied to social good applications, estimating the number of individuals facing human rights abuses (Silverman, 2020).

The project will advance methods for estimating population size, for example, by including population dynamics, or by stratifying the population into subgroups. The project will exploit advancements in Bayesian computation and functional data analysis to develop novel and efficient computational algorithms, this will allow for new models to be successfully implemented.


Bird, S. M., & King, R. (2018). Multiple Systems Estimation (or capture-recapture estimation) to inform public policy. Annual Review of Statistics and Its Application, 5, 95–118.
Otis, D. L., Burnham, K. P., White, G. C., & Anderson, D. R. (1978). Statistical Inference from Capture Data on Closed Animal Populations. Wildlife Monographs, 62, 3–135.
Silverman, B. W. (2020). Multiple‐systems analysis for the quantification of modern slavery: classical and Bayesian approaches. Journal of the Royal Statistical Society. Series A, (Statistics in Society), 183(3), 691–736.

How good is research at University of Birmingham in Mathematical Sciences?

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

Email Now

PhD saved successfully
View saved PhDs