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N. Cressie 447Gourdji, S.M., Mueller, K.L., Schaefer, K., and Michalak, A.M. (2008).Global monthly averaged CO 2 fluxes recovered using a geostatistical inversemodeling approach: 2. Results including auxiliary environmentaldata. Journal of Geophysical Research: Atmospheres, 113,doi:10.1029/2007JD009733.Hastie, T., Tibshirani, R.J., and Friedman, J.H. (2009). The Elements ofStatistical Learning: Data Mining, Inference, and Prediction, 2nd edition.Springer, New York.Houweling, S., Bréon, F.-M., Aben, I., Rödenbeck, C., Gloor, M., Heimann,M., and Ciasis, P. (2004). Inverse modeling of CO 2 sources and sinksusing satellite data: A synthetic inter-comparison of measurement techniquesand their performance as a function of space and time. AtmosphericChemistry and Physics, 4:523–538.Kang, E.L. and Cressie, N. (2011). Bayesian inference for the spatial randomeffects model. Journal of the American Statistical Association, 106:972–983.Kang, E.L. and Cressie, N. (2013). Bayesian hierarchical ANOVA of regionalclimate-change projections from NARCCAP Phase II. International Journalof Applied Earth Observation and Geoinformation, 22:3–15.Kang, E.L., Cressie, N., and Sain, S.R. (2012). Combining outputs from theNARCCAP regional climate models using a Bayesian hierarchical model.Journal of the Royal Statistical Society, Series C, 61:291–313.Katzfuss, M. and Cressie, N. (2011). Spatio-temporal smoothing and EMestimation for massive remote-sensing data sets. Journal of Time SeriesAnalysis, 32:430–446.Katzfuss, M. and Cressie, N. (2012). Bayesian hierarchical spatio-temporalsmoothing for very large datasets. Environmetrics, 23:94–107.Kaufman, C.G. and Sain, S.R. (2010). Bayesian ANOVA modeling usingGaussian process prior distributions. Bayesian Analysis, 5:123–150.Lauvaux, T., Schuh, A.E., Uliasz, M., Richardson, S., Miles, N., Andrews,A.E., Sweeney, C., Diaz, L.I., Martins, D., Shepson, P.B., and Davis, K.(2012). Constraining the CO 2 budget of the corn belt: Exploring uncertaintiesfrom the assumptions in a mesoscale inverse system. AtmosphericChemistry and Physics, 12:337–354.Lindgren, F., Rue, H., and Lindström, J. (2011). An explicit link betweenGaussian fields and Gaussian Markov random fields: The stochastic partialdifferential equation approach (with discussion). Journal of the RoyalStatistical Society, Series B, 73:423–498.

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