I’m an assistant professor in Statistics at the LUMC and the Mathematical Institute of Leiden University.
Sparsity; Causality; Bayesian nonparametrics; Nonparametric regression; Community detection; Survival analysis; Competing risks.
Conference: Survival Analysis for Junior Researchers 2018
SAfJR 2018 will be hosted in Leiden! See the conference website for more information.
11. Posterior Concentration for Bayesian Regression Trees and their Ensembles. [pdf] (with Veronika Rocková)
10. Bayesian Dyadic Trees and Histograms for Regression. [pdf] (with Veronika Rocková, to appear in the NIPS proceedings of 2017)
9. Bayesian Community Detection. [pdf] (with Aad van der Vaart, to appear in Bayesian Analysis)
8. S. van der Pas, P. Grünwald (2018). Almost the Best of Three Worlds: Risk, Consistency and Optional Stopping for the Switch Criterion in Nested Model Selection. Statistica Sinica 28, 229-253. [pdf]
7. B.W. Schreurs, S.L. van der Pas (2018). No Benefit of Arthroscopy in Subacromial Shoulder Pain. The Lancet 391 (10118), 289-291. [pdf]
6. S. van der Pas, B. Szabó and A. van der Vaart (2017). Uncertainty Quantification for the Horseshoe (with Discussion). Bayesian Analysis 12 (4), 1221-1274. [pdf]
5. S. van der Pas, B. Szabó and A. van der Vaart (2017). Adaptive Posterior Contraction Rates for the Horseshoe. Electronic Journal of Statistics 11 (2), 3196-3225. [pdf]
4. S.L. van der Pas, R.G.H.H. Nelissen and M. Fiocco (2017). Patients with Staged Bilateral Total Joint Arthroplasty in Registries: Immortal Time Bias and Methodological Options. Journal of Bone & Joint Surgery – American Volume 99 (15), p e82. [pdf] Link to online journal edition here. Copyright JBJS.
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.
- `Bayesian dyadic trees and histograms for regression’ [poster] (NIPS, Long Beach, December 2017)
- `Posterior concentration for Bayesian regression trees and their ensembles’ [slides] (Workshop on Bayesian and PAC-Bayesian methods, Paris, November 2017)
- `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)