I’m an assistant professor in Statistics at the LUMC and the Mathematical Institute of Leiden University.
Bayesian nonparametrics; Sparsity; Community detection; Survival analysis; Competing risks.
7. Bayesian Community Detection. [pdf] (with Aad van der Vaart)
6. Uncertainty Quantification for the Horseshoe. [pdf] (with Botond Szabó and Aad van der Vaart)
5. Adaptive Posterior Contraction Rates for the Horseshoe. [pdf] (with Botond Szabó and Aad van der Vaart)
4. Almost the Best of Three Worlds: Risk, Consistency and Optional Stopping for the Switch Criterion in Nested Model Selection. [pdf] (with Peter Grünwald)
3. S.L. van der Pas, J.-B. Salomond and J. Schmidt-Hieber (2016). Conditions for Posterior Contraction in the Sparse Normal Means Problem. Electronic Journal of Statistics 10, 976-1000. [pdf]
2. S.L. van der Pas, B.J.K Kleijn and A.W. van der Vaart (2014). The Horseshoe Estimator: Posterior Concentration around Nearly Black Vectors. Electronic Journal of Statistics 8 (2), 2585-2618. [pdf]
1. S. van der Pas (2014). The Normal Road to Geometry: dê in Euclid’s Elements and the Mathematical Competence of His Audience. The Classical Quarterly 64, 558-573. [pdf] Link to online journal edition here. Copyright The Classical Association.
- `Competing risks with time dependent clustering’ [slides] (PTA, London, September 2016)
- `How many needles in the haystack? Adaptive inference and uncertainty quantification for the horseshoe’ [slides] (JSM, Chicago, August 2016)
- `The horseshoe and more general sparsity priors’ [slides] (EYSM, Prague, September 2015)
- `Bayesian community detection’ [slides] (JSM, Seattle, August 2015)
- `The horseshoe estimator: posterior concentration around nearly black vectors’ [slides] (ERCIM, Pisa, December 2014)
- `Conditions for posterior contraction in the sparse normal means problem’ [slides] (Bayes Club, Amsterdam, April 2016)
- `The horseshoe prior for nearly black vectors’ [slides] (Bayes Club, Amsterdam, April 2014)