Browsing Institutt for matematiske fag by Author "Fuglstad, Geir-Arne"
Now showing items 21-37 of 37
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Modeling complex dependence structures in space and time using SPDEs
Berild, Martin Outzen (Doctoral theses at NTNU;2024:345, Doctoral thesis, 2024) -
Modelling Spatial Non-stationarity
Fuglstad, Geir-Arne (Doctoral thesis at NTNU;2015:132, Doctoral thesis, 2015) -
Multivariate Spatial Modeling using SPDEs with Application to Ocean Sampling
Lilleborge, Karina (Master thesis, 2022)I denne masteroppgaven vil vi foreslå multivariate romlige modeller for effektiv prediksjon av temperatur og salinitet i havet. Vi baserer modelleringen og analysen på modelløsninger fra en numerisk havmodell, SINMOD, ... -
Non-parametric Regression in Machine Learning: A Comparison of the Probabilistic and Algorithmic Approach
Nordstrøm, Jonas (Bachelor thesis, 2022)Termen ikke-parametrisk regresjon omhandler et stort antall maskinlærings teknikker som spår fremtidige hendelser av naturlige prosesser ved å bruke funksjoner som er mer fleksible enn deres parametriske motparter. Man kan ... -
Penalised complexity priors in hierarchical models
Kolaas, Vegard (Master thesis, 2022)Hierarkisk-dekomponerings(HD)-a-priori-fordelinger er et rammeverk for å konstruere samtidige a priori fordelinger for variansparametere i latente gaussiske modeller (LGMer) via en tre-struktur som gjenspeiler modellens ... -
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 ... -
Predicting the Risk of Customers Redeeming Loans
Wilberg, Julie Madeleine (Master thesis, 2020)Lån er en nødvendighet for mye av den økonomiske aktiviteten i det moderne samfunn. Långiverne får inntekt fra renter og gebyrer, noe som innebærer at en kunde som innfrir lån representerer et inntektstap. Det er derfor ... -
Predominant regional biophysical cooling from recent land cover changes in Europe
Huang, Bo; Hu, Xiangping; Fuglstad, Geir-Arne; Zhou, Xu; Zhao, Wenwu; Cherubini, Francesco (Journal article; Peer reviewed, 2020)Around 70 Mha of land cover changes (LCCs) occurred in Europe from 1992 to 2015. Despite LCCs being an important driver of regional climate variations, their temperature effects at a continental scale have not yet been ... -
Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge
Hem, Ingeborg Gullikstad; Selle, Maria; Gorjanc, Gregor; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg (Peer reviewed; Journal article, 2020)We propose a novel Bayesian approach that robustifies genomic modeling by leveraging expert knowledge (EK) through prior distributions. The central component is the hierarchical decomposition of phenotypic variation into ... -
Robustifying Bayesian Hierarchical Models Using Intuitive Prior Elicitation
Hem, Ingeborg Gullikstad (Doctoral theses at NTNU;2021:215, Doctoral thesis, 2021) -
Spatial aggregation with respect to a population distribution: Impact on inference
Paige, John; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Wakefield, Jon (Peer reviewed; Journal article, 2022)patial aggregation with respect to a population distribution involves estimating aggregate population quantities based on observations from individuals. In this context, a geostatistical workflow must account for three ... -
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 ... -
Spatially varying anisotropy for Gaussian random fields in three-dimensional space
Berild, Martin Outzen; Fuglstad, Geir-Arne (Journal article; Peer reviewed, 2023)Isotropic covariance structures can be unreasonable for phenomena in three-dimensional spaces. In the ocean, the variability of a response may vary with depth, and ocean currents may lead to spatially varying anisotropy. ... -
Stationary Gaussian stochastic processes
Furset, Simen Knutsen (Bachelor thesis, 2021)Jeg presenterer litt av teorien om stokastiske prosesser. Jeg presenterer et bevis for det spektrale representasjonsteoremet for stasjonære, Gaussiske prosesser og anvender det til å studere andre-ordens, lineære, stokastiske ... -
A Stochastic Locally Diffusive Model with Neural Network-Based Deformations for Global Sea Surface Temperature
Hu, Wenjing; Fuglstad, Geir-Arne; Castruccio, Stefano (Peer reviewed; Journal article, 2021)In this work, we propose a new approach to model large, irregularly distributed spatio-temporal global data via a locally diffusive stochastic partial differential equation (SPDE). The proposed model assumes a local ... -
The Importance of Mesh Resolution When Using the SPDE Approach
Røste, Julie (Master thesis, 2020)Målet med denne oppgaven er å undersøke viktigheten av oppløsningen til triangelnettet (eng: ``Mesh'') for SPDE-tilnærmingen til Lindgren et al. (2011). I denne tilnærmingen approksimeres et romlig Gaussisk felt (GRF) på ...