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An evolutionary spectrum approach to incorporate large-scale geographical descriptors on global processes

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  • Stefano Castruccio
  • Joseph Guinness

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  • Stefano Castruccio & Joseph Guinness, 2017. "An evolutionary spectrum approach to incorporate large-scale geographical descriptors on global processes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(2), pages 329-344, February.
    • Handle: RePEc:bla:jorssc:v:66:y:2017:i:2:p:329-344
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    File URL: http://hdl.handle.net/10.1111/rssc.12167
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    References listed on IDEAS

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    1. Andrew Poppick & Michael L. Stein, 2014. "Using covariates to model dependence in nonstationary, high‐frequency meteorological processes," Environmetrics, John Wiley & Sons, Ltd., vol. 25(5), pages 293-305, August.
    2. Andrew Poppick & Michael L. Stein, 2014. "Erratum: Using covariates to model dependence in nonstationary, high frequency meteorological processes," Environmetrics, John Wiley & Sons, Ltd., vol. 25(7), pages 557-557, November.
    3. Huang, Chunfeng & Zhang, Haimeng & Robeson, Scott M., 2012. "A simplified representation of the covariance structure of axially symmetric processes on the sphere," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1346-1351.
    4. K. Sham Bhat & Murali Haran & Roman Olson & Klaus Keller, 2012. "Inferring likelihoods and climate system characteristics from climate models and multiple tracers," Environmetrics, John Wiley & Sons, Ltd., vol. 23(4), pages 345-362, June.
    5. Joseph Guinness & Michael L. Stein, 2013. "Transformation to approximate independence for locally stationary Gaussian processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(5), pages 574-590, September.
    6. Detlef Vuuren & Jae Edmonds & Mikiko Kainuma & Keywan Riahi & Allison Thomson & Kathy Hibbard & George Hurtt & Tom Kram & Volker Krey & Jean-Francois Lamarque & Toshihiko Masui & Malte Meinshausen & N, 2011. "The representative concentration pathways: an overview," Climatic Change, Springer, vol. 109(1), pages 5-31, November.
    7. Jun, Mikyoung & Knutti, Reto & Nychka, Douglas W, 2008. "Spatial Analysis to Quantify Numerical Model Bias and Dependence," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 934-947.
    8. Finn Lindgren & Håvard Rue & Johan Lindström, 2011. "An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(4), pages 423-498, September.
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    Citations

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    Cited by:

    1. Huang Huang & Stefano Castruccio & Allison H. Baker & Marc G. Genton, 2023. "Saving Storage in Climate Ensembles: A Model-Based Stochastic Approach," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 28(2), pages 324-344, June.
    2. Edwards, Matthew & Castruccio, Stefano & Hammerling, Dorit, 2020. "Marginally parameterized spatio-temporal models and stepwise maximum likelihood estimation," Computational Statistics & Data Analysis, Elsevier, vol. 151(C).
    3. Arafat, Ahmed & Porcu, Emilio & Bevilacqua, Moreno & Mateu, Jorge, 2018. "Equivalence and orthogonality of Gaussian measures on spheres," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 306-318.
    4. Castruccio, Stefano & Genton, Marc G., 2018. "Principles for statistical inference on big spatio-temporal data from climate models," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 92-96.
    5. Matthew Edwards & Stefano Castruccio & Dorit Hammerling, 2019. "A Multivariate Global Spatiotemporal Stochastic Generator for Climate Ensembles," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(3), pages 464-483, September.
    6. Brian J. Reich & Joseph Guinness & Simon N. Vandekar & Russell T. Shinohara & Ana†Maria Staicu, 2018. "Fully Bayesian spectral methods for imaging data," Biometrics, The International Biometric Society, vol. 74(2), pages 645-652, June.
    7. Mikkel Bennedsen & Eric Hillebrand & Siem Jan Koopman, 2020. "A statistical model of the global carbon budget," CREATES Research Papers 2020-18, Department of Economics and Business Economics, Aarhus University.
    8. Guella, Jean Carlo & Menegatto, Valdir Antonio & Porcu, Emilio, 2018. "Strictly positive definite multivariate covariance functions on spheres," Journal of Multivariate Analysis, Elsevier, vol. 166(C), pages 150-159.

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