Allaire, JJ, J. Horner, and Y. Xie et al. 2019. Markdown: Render Markdown with the c Library ’Sundown’.

Bakka, H., H. Rue, and G.-A. Fuglstad et al. 2018. “Spatial Modelling with Inla: A Review,” no. Feb.

Bivand, R., T. Keitt, and B. Rowlingson. 2019. Rgdal: Bindings for the ’Geospatial’ Data Abstraction Library.

Bivand, R. S., E. J. Pebesma, and V. Gomez-Rubio. 2013. Applied Spatial Data Analysis with R. Second Edition. Springer.

Blangiardo, M., and M. Cameletti. 2015. Spatial and Spatio-Temporal Bayesian Models with R-Inla. John Wiley & Sons.

Blumenstock, J., G. Cadamuro, and R. On. 2015. “Predicting Poverty and Wealth from Mobile Phone Metadata.” Science 350 (6264): 1073–6.

Cheng, J., B. Karambelkar, and Y. Xie. 2018. Leaflet: Create Interactive Web Maps with the Javascript ’Leaflet’ Library.

Fick, S. E., and R. J. Hijmans. 2017. “WorldClim 2: New 1-Km Spatial Resolution Climate Surfaces for Global Land Areas.” International Journal of Climatology 37 (12): 4302–15.

F. Lindgren, and H. Rue. 2015. “Bayesian Spatial Modelling with R-INLA.” Journal of Statistical Software 63 (19): 1–25.

Henderson, Storeygard, J. V., and D. N. Weil. 2012. “Measuring Economic Growth from Outer Space.” American Economic Review 102 (2): 994–1028.

Hijmans, R. J. 2019a. Raster: Geographic Data Analysis and Modeling.

———. 2019b. Raster: Geographic Data Analysis and Modeling.

Hunziker, P. 2017. “Velox: Fast Raster Manipulation and Extraction.”

Lindgren, H. Rue, F., and J. Lindström. 2011. “An Explicit Link Between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach (with Discussion).” Journal of the Royal Statistical Society, Series B 73 (4): 423–98.

Martins, T. G., D. Simpson, F. Lindgren, and H. Rue. 2013. “Bayesian Computing with INLA: New Features.” Computational Statistics and Data Analysis 67: 68–83.

Moraga, P. 2019. Geospatial Health Data: Modeling and Visualization with R-Inla and Shiny. Chapman & Hall/CRC Biostatistics Series.

R Core Team. 2018. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.

———. 2020. Package Parallel. Vienna, Austria: R Foundation for Statistical Computing.

Rizzo, M., and G. Szekely. 2018. Energy: E-Statistics: Multivariate Inference via the Energy of Data.

Rue, S. Martino, H., and N. Chopin. 2009. “Approximate Bayesian Inference for Latent Gaussian Models Using Integrated Nested Laplace Approximations (with Discussion).” Journal of the Royal Statistical Society, Series B 71: 319–92.

Sievert, C. 2018. Interactive Web-Based Data Visualization with R, Plotly, and Shiny.

Simpson, D., and H. Rueand A. Riebler et al. 2017. “Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors.” Statistical Science 32 (1): 1–28.

Steele, J. E., P. Roe Sundsøy, and C. et al. Pezzulo. 2017. “Mapping Poverty Using Mobile Phone and Satellite Data.” Journal of the Royal Society Interface 14 (127): 20160690.

Wickham, H., R. François, L. Henry, and K. Müller. 2019. Dplyr: A Grammar of Data Manipulation.

Xie, Y. 2016. Bookdown: Authoring Books and Technical Documents with R Markdown. Boca Raton, Florida: Chapman; Hall/CRC.

Zuur, A. F., E. N. Ieno, and A. A. Saveliev. 2017. Beginner’s Guide to Spatial, Temporal, and Spatial-Temporal Ecological Data Analysis with R-Inla. Vol. 1. Highland Statistics Ltd.