References in zbMATH (referenced in 36 articles )

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  1. Brown, Paul T.; Joshi, Chaitanya; Joe, Stephen; Rue, Håvard: A novel method of marginalisation using low discrepancy sequences for integrated nested Laplace approximations (2021)
  2. Bakar, K. Shuvo: Interpolation of daily rainfall data using censored Bayesian spatially varying model (2020)
  3. Cox, Sonja G.; Kirchner, Kristin: Regularity and convergence analysis in Sobolev and Hölder spaces for generalized Whittle-Matérn fields (2020)
  4. Edwards, Matthew; Castruccio, Stefano; Hammerling, Dorit: Marginally parameterized spatio-temporal models and stepwise maximum likelihood estimation (2020)
  5. Herrmann, Lukas; Kirchner, Kristin; Schwab, Christoph: Multilevel approximation of Gaussian random fields: fast simulation (2020)
  6. Leonelli, Manuele; Riccomagno, Eva; Smith, Jim Q.: Coherent combination of probabilistic outputs for group decision making: an algebraic approach (2020)
  7. Miller, David L.; Glennie, Richard; Seaton, Andrew E.: Understanding the stochastic partial differential equation approach to smoothing (2020)
  8. Steinbuch, Luc; Orton, Thomas G.; Brus, Dick J.: Model-based geostatistics from a Bayesian perspective: investigating area-to-point Kriging with small data sets (2020)
  9. Araki, Takamitsu; Akaho, Shotaro: Spatially multi-scale dynamic factor modeling via sparse estimation (2019)
  10. Barboza, Luis A.; Emile-Geay, Julien; Li, Bo; He, Wan: Efficient reconstructions of Common Era climate via integrated nested Laplace approximations (2019)
  11. Franco-Villoria, Maria; Ventrucci, Massimo; Rue, Håvard: A unified view on Bayesian varying coefficient models (2019)
  12. Lagos-Álvarez, Bernardo; Padilla, Leonardo; Mateu, Jorge; Ferreira, Guillermo: A Kalman filter method for estimation and prediction of space-time data with an autoregressive structure (2019)
  13. Mastrantonio, Gianluca; Lasinio, Giovanna Jona; Pollice, Alessio; Capotorti, Giulia; Teodonio, Lorenzo; Genova, Giulio; Blasi, Carlo: A hierarchical multivariate spatio-temporal model for clustered climate data with annual cycles (2019)
  14. Parrella, Maria Lucia; Albano, Giuseppina; La Rocca, Michele; Perna, Cira: Reconstructing missing data sequences in multivariate time series: an application to environmental data (2019)
  15. Ferreira, Guillermo; Mateu, Jorge; Porcu, Emilio: Spatio-temporal analysis with short- and long-memory dependence: a state-space approach (2018)
  16. Lee, Duncan: A locally adaptive process-convolution model for estimating the health impact of air pollution (2018)
  17. Mosammam, Ali M.; Mateu, Jorge: A penalized likelihood method for nonseparable space-time generalized additive models (2018)
  18. Philipp Otto: spGARCH: An R-Package for Spatial and Spatiotemporal ARCH models (2018) arXiv
  19. Zammit-Mangion, Andrew; Rougier, Jonathan: A sparse linear algebra algorithm for fast computation of prediction variances with Gaussian Markov random fields (2018)
  20. Rao, T. Subba: Book review of: M. Blangiardo and M. Cameletti, Spatial and spatio-temporal Bayesian models with R-INLA (2017)

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