• Flexible modelling of spatial variation in agricultural field trials with the R package INLA 

      Selle, Maria; Steinsland, Ingelin; Gorjanc, Gregor; Hickey, John M. (Journal article; Peer reviewed, 2019)
      The objective of this paper was to fit different established spatial models for analysing agricultural field trials using the open-source R package INLA. Spatial variation is common in field trials, and accounting for it ...
    • Genomic prediction including SNP-specific variance predictors 

      Mouresan, Elena Flavia; Selle, Maria; Rönnegård, Lars (Journal article; Peer reviewed, 2019)
      The increasing amount of available biological information on the markers can be used to inform the models applied for genomic selection to improve predictions. The objective of this study was to propose a general model for ...
    • 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 ...
    • Spatial modelling improves genetic evaluation in smallholder breeding programs 

      Selle, Maria; Steinsland, Ingelin; Powell, Owen; Hickey, John M.; Gorjanc, Gregor (Peer reviewed; Journal article, 2020)
      Background Breeders and geneticists use statistical models to separate genetic and environmental effects on phenotype. A common way to separate these effects is to model a descriptor of an environment, a contemporary group ...