Blar i NTNU Open på forfatter "Martino, Sara"
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A Bayesian Model for Prediction of Heat Consumption
Fardal, Anne Siri (Master thesis, 2019)Når man planlegger utbygging av nye områder, er det viktig med korrekte prognoser for varmeforbruk for å kunne sikre et passende kraftnett. I denne oppgaven presenterer vi latente gaussiske modeller, implementert i R-INLA, ... -
Animal Models and Integrated Nested Laplace Approximations
Holand, Anna Marie; Steinsland, Ingelin; Martino, Sara; Jensen, Henrik (Journal article; Peer reviewed, 2013)Animal models are generalized linear mixed models used in evolutionary biology and animal breeding to identify the genetic part of traits. Integrated Nested Laplace Approximation (INLA) is a methodology for making fast, ... -
Approximate Bayesian Inference for Latent Gaussian Models
Martino, Sara (Doktoravhandlinger ved NTNU, 1503-8181; 2007:214, Doctoral thesis, 2007)This thesis consists of five papers, presented in chronological order. Their content is summarised in this section. Paper I introduces the approximation tool for latent GMRF models and discusses, in particular, the ... -
Bayesian Mortality Modeling with Linearized Integrated Nested Laplace Approximations
Behrens, Helene Randi (Master thesis, 2022)Prediksjon av dødelighet er et viktig verktøy innen for eksempel aktuarviten- skap og demografi. Mange populære dødelighetsmodeller inneholder multiplikative ledd som gjør at de ikke inkluderes i gruppen av modeller der ... -
Correcting for under-reporting of violence against women in Italy using INLA
Wøllo, Sara Elise (Master thesis, 2022)Verdens helseorganisasjon (WHO) anslår at 30% av alle kvinner på verdensbasis har vært usatt for partnervold eller seksuelle overgrep av noen som ikke er en samlivspartnerpartner. I Italia er dette tallet estimert til å ... -
Efficient high-dimensional modelling of temperature and extreme precipitation
Vandeskog, Silius Mortensønn (Doctoral theses at NTNU;2023:379, Doctoral thesis, 2023) -
Importance Sampling with the Integrated Nested Laplace Approximation
Berild, Martin Outzen; Martino, Sara; Gómez-Rubio, Virgilio; Rue, Håvard (Peer reviewed; Journal article, 2022)The integrated nested Laplace approximation (INLA) is a deterministic approach to Bayesian inference on latent Gaussian models (LGMs) and focuses on fast and accurate approximation of posterior marginals for the parameters ... -
Inference on extreme hourly precipitation in Norway using INLA
Mathisen, August Sørli (Master thesis, 2020)I denne oppgaven benyttes et hierarkisk Bayesians modellrammeverk for å studere ekstrem timesnedbør i Oslofjordsområdet. Datapunktene består av observert timesnedbør på 148 værstasjoner. Disse brukes for å studere variasjoner ... -
Integrated Nested Laplace Approximations within Monte Carlo Methods
Berild, Martin Outzen (Master thesis, 2020)Integrated Nested Laplace Approximations (INLA) er en deterministisk metode for å oppnå bayesiansk inferens på latente gaussiske modeller (LGMer) og fokuserer på raske og nøyaktige approksimasjoner av marginale ... -
Integration of presence-only data from several sources: a case study on dolphins' spatial distribution
Martino, Sara; Pace, Daniela Silvia; Moro, Stefano; Casoli, Edoardo; Ventura, Daniele; Frachea, Alessandro; Silvestri, Margherita; Arcangeli, Antonella; Giacomini, Giancarlo; Ardizzone, Giandomenico; Jona Lasinio, Giovanna (Journal article; Peer reviewed, 2021) -
A joint Bayesian framework for missing data and measurement error using integrated nested Laplace approximations
Skarstein, Emma Sofie; Martino, Sara; Muff, Stefanie (Peer reviewed; Journal article, 2023)Measurement error (ME) and missing values in covariates are often unavoidable in disciplines that deal with data, and both problems have separately received considerable attention during the past decades. However, while ... -
Modelling Sub-daily Precipitation Extremes with the Blended Generalised Extreme Value Distribution
Vandeskog, Silius Mortensønn; Martino, Sara; Castro-Camilo, Daniela; Rue, Håvard (Peer reviewed; Journal article, 2022)A new method is proposed for modelling the yearly maxima of sub-daily precipitation, with the aim of producing spatial maps of return level estimates. Yearly precipitation maxima are modelled using a Bayesian hierarchical ... -
Seasonal distribution of an opportunistic apex predator (Tursiops truncatus) in marine coastal habitats of the Western Mediterranean Sea
Pace, Daniela Silvia; Panunzi, Gloria; Arcangeli, Antonella; Moro, Stefano; Jona Lasinio, Giovanna; Martino, Sara (Peer reviewed; Journal article, 2022)Assessing the distribution of marine apex–predators is pivotal to understanding community interactions and defining management goals. However, several challenges arise in both estimates and predictions considering the ... -
Spatial Extreme Value Modelling of Sea Level Data from the Oslo Fjord
Røed, Marion Helen (Master thesis, 2021)Målet for denne oppgaven var å modellere ekstreme havnivå i Oslofjordområdet ved hjelp av en romlig modell. Modeller for ekstreme havnivå blir brukt blant annet til å lage flomkart. Flomkart er nyttig for eksempel for ... -
A spatiotemporal analysis of NO2 concentrations during the Italian 2020 COVID-19 lockdown
Fioravanti, Guido; Cameletti, Michela; Martino, Sara; Cattani, Giorgio; Pisoni, Enrico (Peer reviewed; Journal article, 2022)When a new environmental policy or a specific intervention is taken in order to improve air quality, it is paramount to assess and quantify—in space and time—the effectiveness of the adopted strategy. The lockdown measures ... -
Statistical Methods for the Analysis of Data with a Lower Limit of Detection
Leithe, Sigrid (Master thesis, 2019)I denne oppgaven tar vi opp problemet med å analysere data målt på en kontinuerlig skala med en nedre deteksjonsgrense og null-inflasjon, for univariate, bivariate og longitudinelle data. Vi spesifiserer en sensurert binær ...