Literature reading group
We plan to read important papers of general interest, published in the statistics literature in the last years, and present them in an open seminar. Papers listed below are suggested for reading in our club. If you wish to read and present one of these papers, please let us know. Also, if you have other suggestions, we are happy to add them to the list. Sometimes a group of papers will be presented. Welcome!
The reading group is currently not active. Are you interested in a resurrection? For suggestions: Magne Aldrin
Papers that may be presented later
- Omiros Papaspiliopoulos, Gareth O. Roberts, Martin Sköld (2007). A General Framework for the Parametrization of Hierarchical Models. Statistical Science, Vol. 22, No. 1, 59-73.
- Yun Ju Sung, Charles J. Geyer (2007). Monte Carlo likelihood inference for missing data models. Annals of Statistics, Vol. 35, No. 3, 990-1011.
- Hans R. Künsch (2005). Recursive Monte Carlo filters: Algorithms and theoretical analysis. Annals of Statistics, Vol. 33, No. 5, 1983-2021.
- Edsel A. Peña (2006). Dynamic Modeling and Statistical Analysis of Event Times. Statistical Science, Vol. 21, No. 4, 487-500.
- Peter McCullagh (2008) Sampling bias and logistic models. RSS Ordinary Meeting Wednesday 6 February 2008.
Previous literature reading seminars
- Wednesday 14th May. Ørnulf Borgan presented: Ivy Jansen, Caroline Beunckens, Geert Molenberghs, Geert Verbeke and Craig Mallinckrodt (2006). Analyzing Incomplete Discrete Longitudinal Clinical Trial Data. Statistical Science 2006, Vol. 21, No. 1, 52-69.
- Wednesday 26th March. Lars Holden presented: Bayarri, M.J., Berger, J.O., A., Paulo, R., Sacks, J., Cafeo, J.A., Cavendish, J., Lin, C.H. and Tu, J. (2007). A Framework for Validation of Computer Models. Technometrics, 49, 138-154.
- Thursday 17th January. Ingrid Glad presented: Zhang, J-T. and Chen, J. (2007). Statistical inferences for functional data. Ann. Statist. Volume 35, Number 3, 1052-1079.
- Monday 17th December. Arnoldo Frigessi presented: Tao, T. and Candes, E., The Dantzig selector: statistical estimation when p is much larger than n. To appear in Annals of Statistics.