I attended a talk on recent developments in spatial statistics and while most of the talk was over my head, I did not some resources in the introduction that might be helpful for someone like me who is just learning about this approach.
The two books mentioned were
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Sudipto Banerjee, Bradley P. Carlin, Alan E. Gelfand. Hierarchical Modeling and Analysis for Spatial Data, 2nd edition, Chapman and Hall/CRC. The pulisher’s website has a nice description.
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Noel Cressie, Christopher K. Wikle. Statistics for Spatio-Temporal Data, Wiley. Again, there is a nice description on the publisher’s website.
Edzer Pebesma, Marius Appel, and Daniel N�st have a nice blog, r-spatial, for those interested in learning how to do spatial analysis using R.
Lu Zhang. Nearest Neighbor Gaussian Processes (NNGP) based models in Stan (2018, Jan), is a nicely worked out example of spatial analysis using the Bayesian package, Stan.
https://www.amstat.org/asa/files/pdfs/POL-Statistics-as-a-Scientific-Discipline.pdf https://med.virginia.edu/phs/wp-content/uploads/sites/188/2021/05/TRAppS-Biostat-effort-benchmarks-Apr2021.pdf https://health.ucdavis.edu/ctsc/area/biostatistics/Documents/UCD_Biostat_Effort_Guidelines.pdf