• Havard Rue. Maintainer, author.

  • Finn Lindgren. Author.

  • Elias Teixeira Krainski. Author.

  • Sara Martino. Contributor.

  • Haakon Bakka. Contributor.

  • Daniel Simpson. Contributor.

  • Andrea Riebler. Contributor.

  • Geir-Arne Fuglstad. Contributor.

  • Cristian Chiuchiolo. Contributor.

Citation

Havard Rue, Sara Martino, and Nicholas Chopin (2009), Approximate Bayesian Inference for Latent Gaussian Models Using Integrated Nested Laplace Approximations (with discussion), Journal of the Royal Statistical Society B, 71, 319-392.

@Article{,
  author = {H{\aa}vard Rue and Sara Martino and Nicholas Chopin},
  title = {Approximate {Bayesian} Inference for Latent {Gaussian} Models Using Integrated Nested {Laplace} Approximations (with discussion).},
  journal = {Journal of the Royal Statistical Society B},
  year = {2009},
  volume = {71},
  pages = {319--392},
}

Thiago G. Martins, Daniel Simpson, Finn Lindgren and Havard Rue (2013), Bayesian computing with INLA: New features, Computational Statistics and Data Analysis, 67(2013) 68-83

@Article{,
  title = {Bayesian computing with {INLA}: {N}ew features.},
  author = {Thiago G. Martins and Daniel Simpson and Finn Lindgren and H{\aa}vard Rue},
  year = {2013},
  volume = {67},
  pages = {68--83},
  journal = {Computational Statistics and Data Analysis},
}

Finn Lindgren, Havard Rue, and Johan Lindstrom (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 B, 73(4), 423-498.

@Article{,
  title = {An Explicit Link between {Gaussian} Fields and {Gaussian} {Markov} Random Fields: The Stochastic Partial Differential Equation Approach (with discussion).},
  author = {Finn Lindgren and H{\aa}vard Rue and Johan Lindstr{\"o}m},
  year = {2011},
  volume = {73},
  number = {4},
  pages = {423--498},
  journal = {Journal of the Royal Statistical Society B},
}

Finn Lindgren, Havard Rue (2015). Bayesian Spatial Modelling with R-INLA. Journal of Statistical Software, 63(19), 1-25. URL http://www.jstatsoft.org/v63/i19/.

@Article{,
  title = {Bayesian Spatial Modelling with {R}-{INLA}},
  author = {Finn Lindgren and H{\aa}vard Rue},
  journal = {Journal of Statistical Software},
  year = {2015},
  volume = {63},
  number = {19},
  pages = {1--25},
  url = {http://www.jstatsoft.org/v63/i19/},
}

H. Rue, A. Riebler, S. H. Sorbye, J. B. Illian, D. P. Simpson, and F. K. Lindgren. Bayesian computing with INLA: A review. Annual Reviews of Statistics and Its Applications, 4(March):395-421, 2017. URL http://arxiv.org/abs/1604.00860

@Article{,
  title = {Bayesian computing with {INLA}: {A} review},
  author = {H{\aa}vard Rue and Andrea I. Riebler and Sigrunn H. S{\o}rbye and Janine B. Illian and Daniel P. Simpson and Finn K. Lindgren},
  journal = {Annual Reviews of Statistics and Its Applications},
  year = {2017},
  volume = {4},
  number = {March},
  pages = {395--421},
  url = {http://arxiv.org/abs/1604.00860},
}

H. Bakka, H. Rue, G. A. Fuglstad, A. Riebler, D. Bolin, E. Krainski, D. Simpson, and F. Lindgren. Spatial modelling with R-INLA: A review. Invited extended review, arxiv:1802.06350, 2018.

@Article{,
  title = {Spatial modelling with {INLA}: {A} review},
  author = {Haakon Bakka and H{\aa}vard Rue and Geir-Arne Fuglstad and Andrea I. Riebler and David Bolin and Janine Illian and Elias Krainski and Daniel P. Simpson and Finn K. Lindgren},
  journal = {WIRES (Invited extended review)},
  year = {2018},
  volume = {xx},
  number = {Feb},
  pages = {xx--xx},
  url = {http://arxiv.org/abs/1802.06350},
}

A. De Coninck, B. De Baets, D. Kourounis, F. Verbosio, O. Schenk, S. Maenhout, and J. Fostier, Needles: Toward large-scale genomic prediction with marker-by-environment interaction, Genetics, vol. 203, no. 1, pp. 543-555, 2016.

@Article{,
  title = {Needles: Toward Large-Scale Genomic Prediction with Marker-by-Environment Interaction},
  author = {Arne {De Coninck} and Bernard {De Baets} and Drosos Kourounis and Fabio Verbosio and Olaf Schenk and Steven Maenhout and Jan Fostier},
  volume = {203},
  number = {1},
  pages = {543--555},
  year = {2016},
  doi = {10.1534/genetics.115.179887},
  journal = {Genetics},
  url = {http://dx.doi.org/10.1534/genetics.115.179887},
  eprint = {http://www.genetics.org/content/203/1/543.full.pdf},
}

F. Verbosio, A. D. Coninck, D. Kourounis, and O. Schenk, Enhancing the scalability of selected inversion factorization algorithms in genomic predictions, Journal of Computational Science, vol. 22, no. Supplement C, pp. 99-108, 2017.

@Article{,
  title = {Enhancing the scalability of selected inversion factorization algorithms in genomic prediction},
  author = {Fabio Verbosio and Arne {De Coninck} and Drosos Kourounis and Olaf Schenk},
  journal = {Journal of Computational Science},
  volume = {22},
  number = {Supplement C},
  pages = {99-108},
  year = {2017},
  issn = {1877-7503},
  url = {https://doi.org/10.1016/j.jocs.2017.08.013},
}

D. Kourounis, A. Fuchs, and O. Schenk, Towards the next generation of multiperiod optimal power flow solvers, IEEE Transactions on Power Systems, vol. PP, no. 99, pp. 1-10, 2018.

@Article{,
  title = {Towards the Next Generation of Multiperiod Optimal Power Flow Solvers},
  author = {D. Kourounis and A. Fuchs and O. Schenk},
  journal = {IEEE Transactions on Power Systems},
  year = {2018},
  volume = {PP},
  number = {99},
  pages = {1-10},
  url = {https://doi.org/10.1109/TPWRS.2017.2789187},
}