Haakon Bakka

October 2021

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  High-resolution Bayesian mapping of landslide hazard with unobserved trigger event

  1 min read · Mon, Oct 18 2021

  News

  landslide INLA Log-Gaussian Cox process

  New paper accepted: Opitz, T., Bakka, H., Huser, R. , and Lombardo, L. (2021+), High-resolution Bayesian mapping of landslide hazard with unobserved trigger event , Annals of Applied Statistics, to appear [ arXiv][ PDF preprint ].

August 2021

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  Approximate Bayesian inference for analysis of spatio-temporal flood frequency data

  1 min read · Thu, Aug 5 2021

  News

  Statistics of extremes Spatial extremes extreme weather

  New paper accepted : Jóhannesson, Á. V., Siegert, S., Huser, R. , Bakka, H., and Hrafnkelsson, B. (2021+), Approximate Bayesian inference for analysis of spatio-temporal flood frequency data , Annals of Applied Statistics, to appear [ arXiv][ PDF preprint ]

May 2020

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  New paper accepted in Bayesian Analysis

  1 min read · Mon, May 25 2020

  Spotlight News

  statistics Bayesian Statistics

  New paper accepted: Hrafnkelsson, B., Siegert, S., Huser, R., Bakka, H., and Jóhannesson, Á. V. (2020+), Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models, Bayesian Analysis, to appear [ arXiv].

October 2019

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  Dr. Haakon Bakka presents at the Norwegian Water Resources and Energy Directorate

  1 min read · Mon, Oct 7 2019

  News

  Dr. Haakon Bakka gave a presentation at the Norwegian Water Resources and Energy Directorate on 25 September 2019, on the research performed at KAUST with Prof. Luigi Lombardo and Prof. Raphael Huser on Landslide modelling using R-INLA.

September 2019

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  BayesComp members at the IWSM 2019 in Guimaraes, Portugal

  1 min read · Sun, Sep 8 2019

  News

  Prof. Haavard Rue, Dr. Haakon Bakka and Dr. Janet van Niekerk attended and presented at the International Workshop on Statistical Modelling in July 2019. This workshop brings together experts and young researchers to discuss and collaborate on challenges in statistical modelling.
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  BayesComp members present space-time seminar in Cape Town

  1 min read · Wed, Sep 4 2019

  News

  Prof. Haavard Rue and Dr. Haakon Bakka presented a seminar on spatio-temporal modeling at the University of Cape Town in South Africa in June 2019.
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  BayesComp group present INLA course in South Africa

  1 min read · Wed, Sep 4 2019

  News

  Prof. Haavard Rue, Dr. Haakon Bakka and Dr. Janet van Niekerk presented a four day long INLA training course at the University of South Africa in Florida, Johannesburg during June 2019. The course was designed to impact young staff and PhD students from previously disadvantaged universities in South Africa. The audience gained a lot of skills during this course and the course was very well received.
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  BayesComp members at O'Bayes 2019

  1 min read · Wed, Sep 4 2019

  News

  Prof. Haavard Rue and Dr. Haakon Bakka attended the O'Bayes 2019 conference at University of Warwick, with about 100 participants. Our work were very well recieved [ https://xianblog.wordpress.com/2019/06/30/obayes-19-1-snapshots/], and the concept of Penalized complexity priors seems to be accepted in the community. Dr. Haakon Bakka presented a poster and Prof. Haavard Rue delivered one of the invited talks.
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  BayesComp members present in the European Course in Advanced Statistics on Statistical Analysis for Space-Time Data (ECAS2019)

  1 min read · Wed, Sep 4 2019

  News

  Prof. Haavard Rue and Dr. Haakon Bakka presented a part of the European Course in Advanced Statistics on Statistical Analysis for Space-Time Data (ECAS2019), organized by the Portuguese Statistical Society (SPE) and the Spanish Society of Statistics and Operational Research (SEIO). The course took place in Lisbon, Portugal, on July 15th-17th, 2019. The ECAS courses are intended to achieve postgraduate training in special areas of statistics for (especially 1st year) PhD students, researchers, teachers at universities, and professionals interested in the application of new statistical methods
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  Dr. Haakon Bakka's research visit to Zurich

  1 min read · Wed, Sep 4 2019

  News

  Haakon went to the University of Zurich for two weeks in May 2019 to collaborate with Malgorzata Roos on "Sensitivity and identification quantification by a relative latent model complexity perturbation in the Bayesian meta-analysis" Also in Zurich, Haakon gave a talk at ETH titled "Fundamental ideas of the stochastic partial differential equations approach to defining random effects".
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  BayesComp members at the ISI's WSC 2019 in Kuala Lumpur

  1 min read · Wed, Sep 4 2019

  News

  Prof. Haavard Rue, Dr. Haakon Bakka and Dr. Janet van Niekerk attended the 62 nd World Statistics Congress of the ISI in Kuala Lumpur on 18-23 August 2019 where they presented in invited and contributed paper sessions. This bi-annual meeting brings together major role players from academia, government offices and industry partners.

June 2019

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  New paper accepted in JGR - Earth Surface

  1 min read · Tue, Jun 25 2019

  Spotlight News

  Statistics of extremes Bayesian Statistics

  New accepted paper: Lombardo, L., Bakka, H., Tanyas, H., van Westen, C., Mai, P. M., and Huser, R. (2019+), Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides, Journal of Geophysical Research-Earth Surface [ PDF preprint]

February 2019

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  Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA book

  1 min read · Tue, Feb 19 2019

  News

  INLA statistics xstat research highlights

  Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real