Bilde av Sørbye, Sigrunn Holbek
Bilde av Sørbye, Sigrunn Holbek
Institutt for matematikk og statistikk sigrunn.sorbye@uit.no +4777645504 Tromsø REALF A 218D

Sørbye, Sigrunn Holbek


Førsteamanuensis


  • Nenad Tajsic, Sigrunn Holbek Sørbye, Sophy Nguon, Vannara Sokh, Aymeric Lim :
    Norwegian Open Fracture Management System: Outcomes after 10 Years Working in Low-Resource Settings in Cambodian Hospitals
    Prehospital and Disaster Medicine 2022 ARKIV / DOI
  • Åse Mari Moe, Sigrunn Holbek Sørbye, Laila Arnesdatter Hopstock, Monica Hauger Carlsen, Ola Løvsletten, Elinor Ytterstad :
    Identifying dietary patterns across age, educational level and physical activity level in a cross-sectional study: the Tromsø Study 2015 - 2016
    BMC Nutrition 2022 ARKIV / DOI
  • Martin Wibe Rypdal, Kristoffer Rypdal, Ola Løvsletten, Sigrunn Holbek Sørbye, Elinor Ytterstad, Filippo Maria Bianchi :
    Estimation of Excess Mortality and Years of Life Lost to COVID-19 in Norway and Sweden between March and November 2020
    International Journal of Environmental Research and Public Health (IJERPH) 2021 ARKIV / DOI
  • Sigrunn Holbek Sørbye, Pedro Guilherme Nicolau, Håvard Rue :
    Finite-sample properties of estimators for first and second order autoregressive processes
    Statistical Inference for Stochastic Processes : An International Journal devoted to Time Series Analysis and the Statistics of Continuous Time Processes and Dynamical Systems 2021 ARKIV / DOI
  • Pedro Guilherme Nicolau, Sigrunn Holbek Sørbye, Nigel Yoccoz :
    Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data
    Ecology and Evolution 2020 ARKIV / DOI
  • Eirik Myrvoll-Nilsen, Sigrunn Holbek Sørbye, Hege-Beate Fredriksen, Håvard Rue, Martin Wibe Rypdal :
    Statistical estimation of global surface temperature response to forcing under the assumption of temporal scaling
    Earth System Dynamics 2020 ARKIV / DOI
  • Ola Haug, Thordis Linda Thorarinsdottir, Sigrunn Holbek Sørbye, Christian L.E. Franzke :
    Spatial trend analysis of gridded temperature data at varying spatial scales
    Advances in Statistical Climatology, Meteorology and Oceanography (ASCMO) 2020 ARKIV / DOI
  • Eirik Myrvoll-Nilsen, Hege-Beate Fredriksen, Sigrunn Holbek Sørbye, Martin wibe Rypdal :
    Warming trends and long-range dependent climate variability since year 1900: A Bayesian approach
    Frontiers in Earth Science 2019 ARKIV / DOI
  • Sigrunn Holbek Sørbye, Janine B. Illian, Daniel Peter Simpson, David F. R. P. Burslem, Håvard Rue :
    Careful prior specification avoids incautious inference for log-Gaussian Cox point processes
    The Journal of the Royal Statistical Society, Series C (Applied Statistics) 2018 DOI
  • Martin wibe Rypdal, Hege-Beate Fredriksen, Eirik Myrvoll-Nilsen, Kristoffer Rypdal, Sigrunn Holbek Sørbye :
    Emergent scale invariance and climate sensitivity
    Climate 2018 ARKIV / DOI
  • Sigrunn Holbek Sørbye, Eirik Myrvoll-Nilsen, Håvard Rue :
    An approximate fractional Gaussian noise model with O(n) computational cost
    Statistics and computing 2018 DOI
  • Sigrunn Holbek Sørbye, Håvard Rue :
    Penalised Complexity Priors for Stationary Autoregressive Processes
    Journal of Time Series Analysis 2017 ARKIV / DOI
  • Daniel Simpson, Håvard Rue, Andrea Ingeborg Riebler, Thiago Guerrera Martins, Sigrunn Holbek Sørbye :
    You Just Keep on Pushing My Love over the Borderline: A Rejoinder
    Statistical Science 2017 ARKIV / DOI
  • John Fredrik Strøm, Eva Bonsak Thorstad, Graham Chafe, Sigrunn Holbek Sørbye, David Righton, Audun H. Rikardsen m.fl.:
    Ocean migration of pop-up satellite archival tagged Atlantic salmon from the Miramichi River in Canada
    ICES Journal of Marine Science 13. januar 2017 ARKIV / DOI
  • Daniel Simpson, Håvard Rue, Andrea Ingeborg Riebler, Thiago Guerrera Martins, Sigrunn Holbek Sørbye :
    Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
    Statistical Science 2017 ARKIV / DOI
  • Håvard Rue, Andrea Ingeborg Riebler, Sigrunn Holbek Sørbye, Janine B. Illian, Daniel Peter Simpson, Finn Kristian Lindgren :
    Bayesian Computing with INLA: A Review
    Annual Review of Statistics and Its Application 2017 ARKIV / DOI
  • Sigrunn Holbek Sørbye, Håvard Rue :
    Fractional Gaussian noise: Prior specification and model comparison
    Environmetrics 2017 ARKIV / DOI
  • Daniel Simpson, Janine B. Illian, Finn Lindgren, Sigrunn Holbek Sørbye, Håvard Rue :
    Going off grid: Computationally efficient inference for log-Gaussian Cox processes
    Biometrika 2016 DOI
  • Andrea Ingeborg Riebler, Sigrunn Holbek Sørbye, Daniel Peter Simpson, Håvard Rue :
    An intuitive Bayesian spatial model for disease mapping that accounts for scaling
    Statistical Methods in Medical Research 2016 DOI
  • Sigrunn Holbek Sørbye, Håvard Rue :
    Scaling intrinsic Gaussian Markov random field priors in spatial modelling
    Spatial Statistics 2013 DOI
  • Janine B. Illian, Sara Martino, Sigrunn Holbek Sørbye, Juan Gallego-Fernandez, Maria Zunzunegui, M. Paz Esquivias m.fl.:
    Fitting complex ecological point process models with integrated nested Laplace approximation
    Methods in Ecology and Evolution 2013 DOI
  • Janine Illian, Sigrunn Holbek Sørbye, Håvard Rue :
    A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA)
    Annals of Applied Statistics 2012 FULLTEKST / ARKIV / DOI
  • Pedro Guilherme Nicolau, Sigrunn Holbek Sørbye, Nigel Yoccoz :
    Incorporating sampling error in the estimation of autoregressive coefficients of animal population cycles using capture-recapture data
    2020
  • Sigrunn Holbek Sørbye :
    Statistical models for long-range dependent climate data
    2020
  • Eirik Myrvoll-Nilsen, Sigrunn Holbek Sørbye :
    Incorporating long-range dependency into Bayesian spatio-temporal modeling
    2019
  • Eirik Myrvoll-Nilsen, Sigrunn Holbek Sørbye, Hege-Beate Fredriksen, Martin wibe Rypdal :
    A statistical model for global surface temperature response to radiative forcing with long-range dependent noise
    2019
  • Sigrunn Holbek Sørbye :
    Bayesian analysis of long-range dependent processes with applications in climatology
    2019
  • Sigrunn Holbek Sørbye, Eirik Myrvoll-Nilsen, Martin wibe Rypdal, Hege-Beate Fredriksen, Håvard Rue :
    Bayesian analysis of temperature series accounting for long-range dependence and climate forcing
    2019
  • Sigrunn Holbek Sørbye, Janine B. Illian, Daniel Simpson, David F. R. P. Burslem, Håvard Rue :
    Careful prior specification avoids incautious inference for log-Gaussian Cox point processes
    2018
  • Eirik Myrvoll-Nilsen, Sigrunn Holbek Sørbye, Martin wibe Rypdal, Hege-Beate Fredriksen, Håvard Rue :
    Modeling global surface temperatures in terms of climate forcing and a long-memory stochastic process
    2018
  • Eirik Myrvoll-Nilsen, Sigrunn Holbek Sørbye, Martin wibe Rypdal, Hege-Beate Fredriksen, Håvard Rue :
    Modeling global surface temperatures in terms of climate forcing and a long-memory stochastic process
    2018
  • Sigrunn Holbek Sørbye, Eirik Myrvoll-Nilsen, Håvard Rue :
    An approximate fractional Gaussian noise model with O(n) computational cost
    2017 FULLTEKST
  • Sigrunn Holbek Sørbye, Janine B. Illian, Daniel Simpson, David F. R. P. Burslem :
    Careful prior specification avoids incautious inference for log-Gaussian Cox point processes
    2017 FULLTEKST
  • Ola Haug, Thordis Linda Thorarinsdottir, Sigrunn Holbek Sørbye, Christian Franzke :
    Spatial trend analysis of gridded temperature data sets at varying spatial scales
    2017
  • Sigrunn Holbek Sørbye :
    Efficient approximation of a long memory process
    2017
  • Eirik Myrvoll-Nilsen, Sigrunn Holbek Sørbye, Håvard Rue :
    Computationally efficient Bayesian approximation of fractional Gaussian noise
    2017
  • Sigrunn Holbek Sørbye, Håvard Rue :
    Penalised Complexity Priors for Autoregressive Processes
    2016
  • Sigrunn Holbek Sørbye, Håvard Rue :
    Penalised complexity priors for stationary autoregressive processes
    2016 FULLTEKST
  • Sigrunn Holbek Sørbye :
    Life made easy: Penalised complexity priors
    2016
  • Håvard Rue, Andrea Ingeborg Riebler, Sigrunn Holbek Sørbye, Janine Illian, Daniel Peter Simpson, Finn Kristian Lindgren :
    Bayesian Computing with INLA: A Review
    2016
  • Sigrunn Holbek Sørbye :
    Fractional Gaussian noise models with applications to climate
    2016
  • Andrea Ingeborg Riebler, Daniel Peter Simpson, Sigrunn Holbek Sørbye, Finn Lindgren, Geir-Arne Fuglstad, Håvard Rue :
    Choosing sensible priors for Bayesian spatial analysis in epidemiology
    2015
  • Andrea Ingeborg Riebler, Sigrunn Holbek Sørbye, Daniel Peter Simpson, Håvard Rue :
    An intuitive Bayesian spatial model for disease mapping that accounts for scaling
    2015
  • Andrea Riebler, Daniel Simpson, Sigrunn Holbek Sørbye, Finn Lindgren, Geir-Arne Fuglstad, Håvard Rue :
    Choosing sensible priors for Bayesian spatial analysis in epidemiology
    2015
  • Daniel Peter Simpson, Janine Illian, Sigrunn Holbek Sørbye :
    Spatial Modelling with INLA Short Course
    2014
  • Thiago Guerrera Martins, Daniel Peter Simpson, Andrea Riebler, Håvard Rue, Sigrunn Holbek Sørbye :
    Penalising model component complexity: A principled, practical approach to constructing priors
    2014
  • Andrea Riebler, Thiago Guerrera Martins, Daniel Peter Simpson, Jingyi Guo, Håvard Rue, Sigrunn Holbek Sørbye :
    Penalising model component complexity:A principled, practical approach for constructing priors -- An application to bivariate meta-analysis
    2014
  • Marc Geilhufe, Stein Olav Skrøvseth, Sigrunn Holbek Sørbye, Kassaye Yitbarek Yigzaw, Johan Gustav Bellika, Fred Godtliebsen :
    Spatio-temporal modeling of communicable diseases: A case study of North Norway
    2012
  • Sigrunn Holbek Sørbye, Ditte Katrine Hendrichsen, Janine Illian, Håvard Rue :
    Spatio-temporal modeling of replicated point patterns
    2012
  • Sigrunn Holbek Sørbye :
    Analysis of spatial point patterns using INLA
    2012

  • De 50 siste resultatene fra Cristin vises på siden. Se alle arbeider i Cristin her →


    Forskningsinteresser

    Statistical modeling and analysis of time series and spatial data.

    Bayesian computation using the methodology of integrated nested Laplace approximation (INLA).





    REALF A 218D

    Klikk for større kart