Lecture Notes
Recommended Texts
Wikle C., Zammit-Mangion A., Cressie N. 2019. Spatio-temporal statistics with R. Chapman & Hall/CRC. [book website] [pdf]
Main text for this class.
Cressie, N., Wikle, C. 2011. Statistics for Spatio-temporal Data. [link]
First book fully dedicated to spatio-temporal statistics. This book is a classic in the field, but a bit more technical than Wikle et al. (2019) and doesn't contain worked examples.
Cressie, N. 1993. Statistics for Spatial Data (Revised edition). [link]
This is a big book and a classic in the field of spatial statistics. As correctly noted by the author: "This [1990] may be the last time spatial Statistics will be squeezed between two covers."
Hooten, M., Hefley. T. Bringing Bayesian Models to Life. [link]
This book shows how to build a wide variety of Bayesian models from scratch. Contains many worked examples in R.
Hooten, M. Johnson, D., McClintock, B., Morales B. Animal Movement: Statistical Models for Telemetry Data. [link]
This is a fantastic book about modeling position data and trajectories of animals.
Banerjee, S., Carlin, B., Gelfand, A. 2014. Hierarchical Modeling and Analysis for Spatial Data. [link]
Great reference for Bayesian Hierarchical modeling of spatial data. Contains worked examples using WinBUGS.
Supplementary Text
Xie Y., Allaire J., Grolemund G. (2018) R Markdown: the definitive guide. CRC Press [bookdown] [pdf]
Perpiñán, O. (2018) Displaying time series, spatial, and spatio-temporal data with R. (second edition). CRC Press. [link]
This is a comprehensive and recently updated text that will save you a lot of time when trying to make nice plots.
Fieller, N. (2015) Basics of Matrix Algebra for Statistics with R. Chapman and Hall/CRC [link]
Concise introduction accessible to all students.
Banerjee, S. and Roy, A (2015) Linear Algebra and Matrix Analysis for Statistics. Chapman and Hall/CRC [link]
Complete reference for statistics graduate students.
Gelman A. et al. 2013. Bayesian data analysis. Third edition. [pdf]
Recommended Software