Research interests

• Inference of stochastic processes using Bayesian statistics with biology and finance applications
• Monte Carlo methods in statistics
• Stability theory for Markov chains

Selected publications

• Samia, N. & Stramer, O. (2019). Bayesian inference of panels of threshold autoregressive time.
• Samia, N., Stramer, O., Stenseth, N., Saitoh, T., Rosen, O. & Bertolacci, M. (2019). Climate-driven context-dependent structure of population cycles.
• Stramer, O., Shen, X. & Bognar, M. (2017). Bayesian inference for Heston-STAR models. Statistics and Computing, 27(2), 331-348. DOI: DOI:10.1007/s11222-015-9625-y.
• Stramer, O., Roberts, G. & Papaspiliopoulos, O. (2013). Data augmentation for diffusions. Journal of Computational and Graphical Statistics, 22(3), 665-688.
• Samia, N. I., Stramer, O., Stenseth, N. C. & Saitoh, T. (2012). Bayesian inference of panels of threshold autoregressive time series.
• Stramer, O., Bognar, M. (2011). Bayesian inference for irreducible diffusion processes using the pseudo- marginal approach. Bayesian Analysis, 6(2), 179–358.
• Casella, B., Roberts, G. & Stramer, O. (2011). Stability of partially implicit Langevin schemes and their MCMC variants. Methodology & Computing in Applied Probability, 13(4), 835–854.
• STRAMER, O., Bognar, M. & Schneider, P. (2010). Bayesian inference for discretely sampled Markov processes with closed-Form likelihood expansions. Journal of Financial Econometrics, 8, 450-480.
• Stramer, O. (2008). Asymptotics of efficient Monte Carlo estimations for the transition Density of multivariate diffusion processes. Refereed procedure volume for the 2008 international workshop on Applied Probability.
• Stramer, O., Yan, J. (2007). Asymptotics of an efficient Monte Carlo estimation for the transition density of diffusion processes. Methodology & Computing in Applied Probability, 9(4), 483-496.