Browsing NTNU Open by Author "Steinsland, Ingelin"
Now showing items 1-20 of 70
-
A Bayesian Model for Area and Point Predictions - A Case Study of Predictions of Annual Precipitation and Runoff in the Voss Area.
Roksvåg, Thea Julie Thømt (Master thesis, 2016)In this work we perform predictions of annual precipitation and runoff by spatial interpolation. For this purpose, we utilise both point observations of precipitation and/or area observations of runoff from several years. ... -
A Framework for Constructing and Evaluating Probabilistic Forecasts of Electricity Prices: A Case Study of the Nord Pool Market
Stenshorne, Kim (Master thesis, 2011)A framework for a 10-day ahead probabilistic forecast based on a deterministic model is proposed. The framework is demonstrated on the system price of the Nord Pool electricity market. The framework consists of a two-component ... -
A shared Parameter Model Accounting for Dropout Not at Random: A Case Study on Blood Pressure in the HUNT Study
Hofman, Aurora Christine (Master thesis, 2022)I dette arbeidet foreslår vi å tilpasse en felles parametermodell (SPM) i et Bayesianske rammeverket for å ta hensyn til manglende data på grunn av frafall i befolkningsbaserte helseundersøkelser. Vi bruker data fra helse ... -
A shared parameter model accounting for non-ignorable missing data due to dropout: Modelling of blood pressure based on the HUNT Study
Espeland, Lars Fredrik (Master thesis, 2020)I denne oppgaven blir en delt-parameter-modell foreslått for å ta hensyn til ikke-tilfeldige manglende verdier (missing not at random, MNAR) i oppfølgingsstudier. Denne modellen er motivert av, og evaluert på, en stor ... -
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 ... -
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, ... -
Bayesian Calibration and Inference for Multiple Machines
Lam, Hong-Tan (Master thesis, 2019)I denne oppgaven, blir simuleringsmodeller, også kalt simulatorer, brukt til utføre prediksjon på maskiner. En av utfordringene med å gjøre prediksjon med simuleringsmodeller, er at de ikke fullt beskriver den sanne prosessen ... -
Bayesian Calibration for Modelling the Cardiovascular System Using the Two Element Windkessel Model
Olsen, Helene Minge (Master thesis, 2022)Denne oppgaven utforsker egenskapene til Windkessel-modellene basert på syntetiske simuleringsstudier, og er en del av det tverrfaglige prosjektet "My Medical Digital Twin" ved NTNU. Windkessel-modellene estimerer de globale ... -
Bayesian Calibration of Imperfect Computer Models using Physics-Informed Priors
Spitieris, Michail; Steinsland, Ingelin (Peer reviewed; Journal article, 2023)We introduce a computational e_cient data-driven framework suitable for quantifying the uncertainty in physical parameters and model formulation of computer models, represented by di_erential equations. We construct ... -
Bayesian Model Averaging for Wind Speed Ensemble Forecasts Using Wind Speed and Direction
Eide, Siri Sofie; Bremnes, John Bjørnar; Steinsland, Ingelin (Journal article; Peer reviewed, 2017)In this paper, probabilistic wind speed forecasts are constructed based on ensemble numerical weather prediction (NWP) forecasts for both wind speed and wind direction. Including other NWP variables in addition to the one ... -
Bayesian Model Averaging Using Varying Coefficient Regression and Climatology Cumulative Probability Regression - A Case Study of Postprocessing Hydrological Ensembles from Osali
Kleiven, Andreas (Master thesis, 2017)Bayesian Model Averaging Using Varying Coefficient Regression and Climatology Cumulative Probability Regression. -
Benefits of spatio-temporal modelling for short term wind power forecasting at both individual and aggregated levels
Lenzi, Amanda; Steinsland, Ingelin; Pinson, Pierre (Research report, 2017)The share of wind energy in total installed power capacity has grown rapidly in recent years around the world. Producing accurate and reliable forecasts of wind power production, together with a quantification of the ... -
Benefits of spatiotemporal modeling for short-term wind power forecasting at both individual and aggregated levels
Lenzi, Amanda; Steinsland, Ingelin; Pinson, Pierre (Journal article; Peer reviewed, 2018)The share of wind energy in total installed power capacity has grown rapidly in recent years. Producing accurate and reliable forecasts of wind power production, together with a quantification of the uncertainty, is essential ... -
Bivariate Bayesian Model Averaging and Ensemble Model Output Statistics: With a Case Study of Ensemble Temperature Forecasts in Trondheim
Prokosch, Jorinde (Master thesis, 2013)In this study a bivariate Bayesian model averaging (BMA) and Ensemble model output statistics (EMOS) technique for ensemble temperature forecasts are proposed to account for lead time dependencies between errors. Also ... -
Climatology Cumulative Probability Regression: A Postprocessing Methodology Based on Climatology and Deterministic Forecasts, With a Case Study of Streamflow Forecasts at Osali
Borhaug, Johanne (Master thesis, 2014)This study introduce a new postprocessing methodology for constructing probabilistic forecasts based on climatology and deterministic forecasts. The Climatology Cumulative Probability Regression (CCPR) methodology is based ... -
Closure Law Model Uncertainty Quantification
Strand, Andreas; Kjølaas, Jørn; Bergstrøm, Trond Harald; Steinsland, Ingelin; Hellevik, Leif Rune (Peer reviewed; Journal article, 2021)The prediction uncertainty in simulators for industrial processes is due to uncertainties in the input variables and uncertainties in specification of the models, in particular the closure laws. In this work, the uncertainty ... -
Data-driven Avalanche Forecasting - Using automatic weather stations to build a data-driven decision support system for avalanche forecasting
Hennum, Anders Asheim (Master thesis, 2016)In this paper, a decision support system for avalanche forecasting based on data from automatic weather stations is developed and tested. 17 years of avalanche and weather observations from Senja in Northern Norway are ... -
Development of risk models of incident hypertension using machine learning on the HUNT study data
Schjerven, Filip Emil; Ingeström, Emma Maria Lovisa; Steinsland, Ingelin; Lindseth, Frank (Journal article; Peer reviewed, 2024)In this study, we aimed to create an 11-year hypertension risk prediction model using data from the Trøndelag Health (HUNT) Study in Norway, involving 17 852 individuals (20–85 years; 38% male; 24% incidence rate) with ... -
Efficient high-dimensional modelling of temperature and extreme precipitation
Vandeskog, Silius Mortensønn (Doctoral theses at NTNU;2023:379, Doctoral thesis, 2023) -
Estimation of annual runoff by exploiting long-term spatial patterns and short records within a geostatistical framework
Roksvåg, Thea; Steinsland, Ingelin; Engeland, Kolbjørn (Peer reviewed; Journal article, 2020)In this article, we present a Bayesian geostatistical framework that is particularly suitable for interpolation of hydrological data when the available dataset is sparse and includes both long and short records of runoff. ...