Bayesian geostatistical modelling with informative sampling locations.

@article{Pati2011BayesianGM,
  title={Bayesian geostatistical modelling with informative sampling locations.},
  author={Debdeep Pati and Brian J. Reich and David B. Dunson},
  journal={Biometrika},
  year={2011},
  volume={98 1},
  pages={35-48}
}
We consider geostatistical models that allow the locations at which data are collected to be informative about the outcomes. A Bayesian approach is proposed, which models the locations using a log Gaussian Cox process, while modelling the outcomes conditionally on the locations as Gaussian with a Gaussian process spatial random effect and adjustment for the location intensity process. We prove posterior propriety under an improper prior on the parameter controlling the degree of informative… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.
8 Citations
20 References
Similar Papers

References

Publications referenced by this paper.
Showing 1-10 of 20 references

Geostatistical inference under preferential sampling (with discussion)

  • P. 1969–87. DIGGLE, R. MENEZES, SU T.
  • Appl . Statist
  • 2010
Highly Influential
3 Excerpts

A class of convolution - based models for spatio - temporal processes with non - separable covariance structure

  • A. RODRIGUES, P. DIGGLE
  • Scand . J . Statist
  • 2010
1 Excerpt

Modeling marked point patterns by intensitymarked Cox processes

  • L. P. Ho
  • Statistics and Probability Letters
  • 2009

Assessing spatial dependency under non - standard sampling

  • R. Menezes.
  • 2008

Modelling marked point patterns by intensity-marked Cox processes

  • Issues, HO L.37–56., D. STOYAN
  • Statist . Prob . Lett
  • 2008

Alternative posterior consistency results in nonparametric binary regression using Gaussian process

  • T. Compostela. CHOI
  • 2007
1 Excerpt

Alternative posterior consistency results in nonparametric binary regression using Gaussian process priors

  • T. CHOI
  • J . Statist . Plan . Infer
  • 2007
1 Excerpt

Similar Papers

Loading similar papers…