Modeling spatial and spatio-temporal data over varying support

The Stat 8750.06 working group on Spatial Statistics and Environmental Statistics will be meeting this semester on every second Monday from 12.40-1.35pm in Cockins 212.

Students: Please register for the 1 semester hour course if you are interested in participating in the working group.

Schedule

1. Sep 14, 2015: Spatial change-of-support and misalignment problems 1 (Peter Craigmile)
   References:
   • C. A. Gotway and L. J. Young. Combining incompatible spatial data. Journal of the American Statistical Association, 97:632–648, 2002.
   • A. E. Gelfand, L. Zhu, and B. P. Carlin. On the change of support problem for spatio-temporal data. Biostatistics, 2:31–45, 2001.
2. Sep 28, 2015: Spatial change-of-support and misalignment problems 2 (Peter Craigmile)
1. C. Calder, P. Craigmile, and J. Zhang. Regional spatial modeling of topsoil geochemistry. Biometrics, 65:206–215, 2009.
3. Oct 12, 2015: Preferential sampling (Marie Ozanne + Justin Strait)
1. P. J. Diggle and R. Menezes and T.-l. Su (2010), Geostatistical inference under preferential sampling, Journal of the Royal Statistical Society, Series C (Applied Statistics), 59, 191-232.

   (You might also want to take a look at R. Menezes da Mota Leite (2005), Assessing spatial dependency under non-standard sampling, Ph.D. Dissertation, Universidad de Santiago de Compostela.)

2. D. Pati and B. J. Reich and D. B. Dunson (2011), Bayesian geostatistical modelling with informative sampling locations, Biometrika, 98, 35-48.

3. A. E. Gelfand and S. K. Sahu and D. M. Holland (2012), On the effect of preferential sampling in spatial prediction, Environmetric, 23, 565-578.

4. A. Lee and A. Szpiro and S. Y. Kim and L. Sheppard (2015), Impact of preferential sampling on exposure prediction and health effect inference in the context of air pollution epidemiology, Environmetrics.

4. Oct 26, 2015: An introduction to statistical data assimilation (Radu Herbei)
• C. K. Wikle and L. M. Berliner (2007), A Bayesian tutorial for data assimilation, Physica D, 230, 1-16.

5. Nov 3, 2015, 12.40pm, Cockins 212 (different date): In Stat 8750.02: Design of Physical and Computer Experiments, Oksana Chkrebtii will discuss the paper A statistical overview and perspectives on data assimilation for marine biogeochemical models.
6. Nov 9 2015, No meeting.
7. Nov 12, 2015, 3pm, Cockins 240 (different date, time and location): Guest lecture by Mike Dowd, Dalhousie University
8. Nov 23, 2015: Geographic variation in vaccine efficacy: application of spatial regression models to randomized controlled trials (Elisabeth Dowling Root, Department of Geography and Division of Epidemiology)
• E D Root, el al. (2014), Distance to health services affects local-level vaccine efficacy for pneumococcal conjugate vaccine (PCV) among rural Filipino children, Proceedings of the National Academy of Sciences, 111, 3520–3525
• M. Emcha, et al. (2007), Cover image Efficacy calculation in randomized trials: Global or local measures?, Health and Place, 13 Pages 238–248.
• M. M. Wall (2004), A close look at the spatial structure implied by the CAR and SAR models, Journal of Statistical Planning and Inference, 121, 311-324
9. Dec 7, 2015: Particle MCMC (Meng Li + Corey Smith)
• Andrieu and A. Doucet and R. Holenstein (2010), Particle Markov chain Monte Carlo methods, Journal of the Royal Statistical Society, Series B, 72 269-342.