Bibliography

Here we’ll list some useful papers and books on the topics covered in the course.

Books

• Wood, S. N. (2006). Generalized Additive Models. CRC Press.
• Ruppert, D., Wand, M. P., & Carroll, R. J. (2003). Semiparametric Regression. Cambridge University Press.
• Hastie, T. J., & Tibshirani, R. J. (1990). Generalized Additive Models. Taylor & Francis.

General

• Wood, S. N. (2003). Thin plate regression splines. Journal of the Royal Statistical Society: Series B (Statistical Methodology).
• Reiss, P. T., & Ogden, R. T. (2009). Smoothing parameter selection for a class of semiparametric linear models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 71(2), 505–523.
• Wood, S. N. (2011). Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 73(1), 3–36. http://doi.org/10.1111/j.1467-9868.2010.00749.x
• Wood, S. N., Pya, N., & Säfken, B. (2016). Smoothing parameter and model selection for general smooth models. Journal of the American Statistical Association, 1–45. http://doi.org/10.1080/01621459.2016.1180986

Uncertainty

• Marra, G., & Wood, S. N. (2012). Coverage Properties of Confidence Intervals for Generalized Additive Model Components. Scandinavian Journal of Statistics, 39(1), 53–74. http://doi.org/10.1111/j.1467-9469.2011.00760
• Simpson, G. L. (2011) Additive modelling and the HadCRUT3v global mean temperature series. fromthebottomoftheheap.net http://www.fromthebottomoftheheap.net/2011/06/12/additive-modelling-and-the-hadcrut3v-global-mean-temperature-series/
• Simpson, G. L. (2014) Simultaneous confidence intervals for derivatives of splines in GAMs. fromthebottomoftheheap.net http://www.fromthebottomoftheheap.net/2014/06/16/simultaneous-confidence-intervals-for-derivatives/

Model checking

• Dunn, P. K., & Smyth, G. K. (1996). Randomized Quantile Residuals. Journal of Computational and Graphical Statistics, 5(3), 236–244. http://doi.org/10.1080/10618600.1996.10477470

Response distributions

Tweedie

• Foster, S. D., & Bravington, M. V. (2012). A Poisson–Gamma model for analysis of ecological non-negative continuous data. Environmental and Ecological Statistics, 20(4), 533–552. http://doi.org/10.1007/s10651-012-0233-0
• Shono, H. (2008). Application of the Tweedie distribution to zero-catch data in CPUE analysis. Fisheries Research, 93(1-2), 154–162. http://doi.org/10.1016/j.fishres.2008.03.006

Applications

Species distribution modelling

• Augustin, N. H., Musio, M., Wilpert, von, K., Kublin, E., Wood, S. N., & Schumacher, M. (2009). Modeling Spatiotemporal Forest Health Monitoring Data. Journal of the American Statistical Association, 104(487), 899–911. http://doi.org/10.1198/jasa.2009.ap07058
• Augustin, N. H., Trenkel, V. M., Wood, S. N., & Lorance, P. (2013). Space-time modelling of blue ling for fisheries stock management. Environmetrics, 24(2), 109–119. http://doi.org/10.1002/env.2196
• Miller, D. L., Burt, M. L., Rexstad, E. A., & Thomas, L. (2013). Spatial models for distance sampling data: recent developments and future directions. Methods in Ecology and Evolution, 4(11), 1001–1010. http://doi.org/10.1111/2041-210X.12105
• Wood, S. N., Bravington, M. V., & Hedley, S. L. (2008). Soap film smoothing. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70(5), 931–955. http://doi.org/10.1111/j.1467-9868.2008.00665.x
• Course notes from Dave’s spatial modelling course at Duke available here