• A Comparison of Model-Based and Design-Based Methods for Spatial Modelling Using Complex Survey Data 

      Saghagen, Marte Marie (Master thesis, 2019)
      I de siste årene har det blitt gjore store framskritt i estimering av barnedødelighet på subnasjonalt nivå med survey data. De mest brukte metodene er design-baserte, som er enkle å implementere og produserer estimater som ...
    • A Statistical Approach to Spatial Mapping of Temperature Change 

      Hem, Ingeborg Gullikstad (Master thesis, 2017)
      In this thesis, spatio-temporal temperature trends are estimated based on monthly average temperatures from 503 observation locations in the southern half of Norway. The time period studied is 1960 to 2016. A latent Gaussian ...
    • Assessing comorbidity and correlates of wasting and stunting among children in Somalia using cross-sectional household surveys: 2007 to 2010 

      Kinyoki, Damaris K.; Kandala, Ngianga-Bakwin; Manda, Samuel O.; Krainski, Elias Teixeira; Fuglstad, Geir-Arne; Moloney, Grainne M.; Berkley, James A.; Noor, Abdisalan M. (Journal article; Peer reviewed, 2016)
      Objective: Wasting and stunting may occur together at the individual child level; however, their shared geographic distribution and correlates remain unexplored. Understanding shared and separate correlates may inform ...
    • Compression of Climate Simulations with a Nonstationary Global Spatio-Temporal SPDE Model 

      Fuglstad, Geir-Arne; Castruccio, Stefano (Peer reviewed; Journal article, 2020)
      Modern climate models pose an ever-increasing storage burden to computational facilities, and the upcoming generation of global simulations from the next Intergovernmental Panel on Climate Change will require a substantial ...
    • Constructing Priors that Penalize the Complexity of Gaussian Random Fields 

      Fuglstad, Geir-Arne; Simpson, Daniel; Lindgren, Finn; Rue, Håvard (Journal article; Peer reviewed, 2018)
      Priors are important for achieving proper posteriors with physically meaningful covariance structures for Gaussian random fields (GRFs) since the likelihood typically only provides limited information about the covariance ...
    • Estimating under-five mortality in space and time in a developing world context 

      Wakefield, Jon; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Godwin, Jessica; Wilson, Katie; Clark, Samuel J. (Journal article; Peer reviewed, 2018)
      Accurate estimates of the under-five mortality rate in a developing world context are a key barometer of the health of a nation. This paper describes a new model to analyze survey data on mortality in this context. We are ...
    • Forecasting Child Mortality while Accounting for Complex Survey Design 

      Vik, Hedda Hognedatter Bjørnebye (Master thesis, 2019)
      Barnedødelighetsrater er viktige indikatorer på en nasjons helse. FNs tusenårsmål (MDG) og bærekraftsmål (SDG) fokuserer på å redusere barnedødelighet. Man trenger nøyaktige estimater og prediksjoner for nyfødtdødelighet ...
    • Intuitive Joint Priors for Variance Parameters 

      Fuglstad, Geir-Arne; Hem, Ingeborg Gullikstad; Knight, Alexander; Rue, Håvard; Riebler, Andrea Ingeborg (Journal article; Peer reviewed, 2019)
      Variance parameters in additive models are typically assigned independent priors that do not account for model structure. We present a new framework for prior selection based on a hierarchical decomposition of the total ...
    • Landscape relatedness: detecting contemporary fine-scale spatial structure in wild populations 

      Norman, Anita J.; Stronen, Astrid V.; Fuglstad, Geir-Arne; Ruiz-Gonzalez, Aritz; Kindberg, Jonas; Street, Nathaniel R.; Spong, Göran (Journal article; Peer reviewed, 2016)
      Context: Methods for detecting contemporary, fine-scale population genetic structure in continuous populations are scarce. Yet such methods are vital for ecological and conservation studies, particularly under a changing ...
    • Modelling Spatial Non-stationarity 

      Fuglstad, Geir-Arne (Doctoral thesis at NTNU;2015:132, Doctoral thesis, 2015)
    • Predicting soil properties in the Canadian boreal forest with limited data: Comparison of spatial and non-spatial statistical approaches 

      Beguin, Julien; Fuglstad, Geir-Arne; Mansuy, Nicolas; Pare, David (Journal article; Peer reviewed, 2017)
      Digital soil mapping (DSM) involves the use of georeferenced information and statistical models to map predictions and uncertainties related to soil properties. Many remote regions of the globe, such as boreal forest ...
    • Spatial Modelling and Inference with SPDE-based GMRFs 

      Fuglstad, Geir-Arne (Master thesis, 2011)
      In recent years, stochastic partial differential equations (SPDEs) have been shown to provide a usefulway of specifying some classes of Gaussian random fields. The use of an SPDEallows for the construction of a Gaussian ...
    • Spatial modelling with R-INLA: A review 

      Bakka, Haakon; Rue, Håvard; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Bolin, David; Illian, Janine B.; Krainski, Elias Teixeira; Simpson, Daniel; Lindgren, Finn (Journal article; Peer reviewed, 2018)
      Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically‐sized datasets from scratch is ...