Blar i NHH Brage på forfatter "Berentsen, Geir Drage"
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A gentle tutorial on accelerated parameter and confidence interval estimation for hidden Markov models using Template Model Builder
Bacri, Timothee Raphael Ferdinand; Berentsen, Geir Drage; Bulla, Jan; Hølleland, Sondre Nedreås (Peer reviewed; Journal article, 2022)A very common way to estimate the parameters of a hidden Markov model (HMM) is the relatively straightforward computation of maximum likelihood (ML) estimates. For this task, most users rely on user-friendly implementation ... -
Analysis of Norwegian Offshore Wind Power Production : Ranking wind farm locations using a composite index method
Wallevik, Eirik Hjellvik; Klock, Henrik Krohn (Master thesis, 2022)This thesis studies wind power production within the Norwegian Economic Zone, and analyzes the potential production of wind power farm locations outlined by the Norwegian Water Resource and Energy Directorate. Offshore ... -
Assessing Offshore Wind Farm Placements in Norway Is NVE’s current plan optimal – or can we do better?
Osnes, Andreas; Nesheim, Sindre Houge (Master thesis, 2022)Over the last decade, offshore wind has received increased attention due to global warming and the increase in energy demand. Therefore, it is of the highest interest to develop more renewable energy production to satisfy ... -
Beyond the Gale: Parametric Insurance Pricing for Offshore Wind: Applications of Hierarchical Bayesian Methods, Markov Chain Monte Carlo and Copula-Based Risk Assessment on Zero Generation Events
Stølsnes, Simen; Hellesøy, Theodor (Master thesis, 2023)This thesis introduces an innovative pricing model for parametric insurance of zerogeneration events at offshore wind farms, mainly focusing on the Norwegian shelf. The model employs a Hierarchical Bayesian approach to ... -
Climate change and its effects on Norwegian potato production:How to counteract the negative impacts of soil compaction by implementing a predictive simulation model
Vassbotn, Eirik; Sandok, Karoline Erika Wigestrand (Master thesis, 2021)In a world where the population is immersed in the negative effects of climate change, and the extreme weather conditions that emerge, several papers discuss its effect on agricultural practices, and which innovations ... -
Computational issues in parameter estimation for hidden Markov models with template model builder
Bacri, Timothee Raphael Ferdinand; Berentsen, Geir Drage; Bulla, Jan; Støve, Bård (Peer reviewed; Journal article, 2023)A popular way to estimate the parameters of a hidden Markov model (HMM) is direct numerical maximization (DNM) of the (log-)likelihood function. The advantages of employing the TMB [Kristensen K, Nielsen A, Berg C, et al. ... -
Computational issues in parameter estimation for hidden Markov models with template model builder
Bacri, Timothee Raphael Ferdinand; Berentsen, Geir Drage; Bulla, Jan; Støve, Bård (Peer reviewed; Journal article, 2023)A popular way to estimate the parameters of a hidden Markov model (HMM) is direct numerical maximization (DNM) of the (log-)likelihood function. The advantages of employing the TMB [Kristensen K, Nielsen A, Berg C, et al. ... -
Distinguishing potential child insurance customers : a statistical investigation
Altunel, Çaglar; Holte, Hallvard (Master thesis, 2020)In this thesis we try to illuminate possible reasons why the launch of a more affordable child insurance product by an established Norwegian insurance company failed to live up to the company’s expectations. We use three ... -
Interpreting machine learning models: An overview with applications to German real estate data
Grimen, Andreas; Ibrahimli, Huseyn (Master thesis, 2021)Machine learning models have demonstrated huge improvement in examining complex patterns, which allow them to make predictions about the unobserved data. While the accuracy of these models increases over time, so does ... -
Local Lead–Lag Relationships and Nonlinear Granger Causality: An Empirical Analysis
Otneim, Håkon; Berentsen, Geir Drage; Tjøstheim, Dag Bjarne (Peer reviewed; Journal article, 2022)The Granger causality test is essential for detecting lead–lag relationships between time series. Traditionally, one uses a linear version of the test, essentially based on a linear time series regression, itself being ... -
Modelling clusters of corporate defaults: Regime-switching models significantly reduce the contagion source
Berentsen, Geir Drage; Bulla, Jan; Maruotti, Antonello; Støve, Bård (Peer reviewed; Journal article, 2022)In this paper, we report robust evidence that the process of corporate defaults is time-dependent and can be modelled by extending an autoregressive count time series model class via the introduction of regime-switching. ... -
Optimal Allocation of Norwegian Offshore Wind Power : A Copula Approach : How can a thoughtful placement of offshore wind parks reduce variability in production output?
Alfsvåg, Henrik Heltne; Sollie, Sander (Master thesis, 2023)This thesis investigates how to optimize stable wind production along the coast of Norway. The research is carried out by studying how well a compound dependency model, consisting of a time series and copula model, for ... -
Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations
Sleire, Anders Daasvand; Støve, Bård; Otneim, Håkon; Berentsen, Geir Drage; Tjøstheim, Dag Bjarne; Haugen, Sverre Hauso (Peer reviewed; Journal article, 2021)It is well known that there are asymmetric dependence structures between financial returns. This paper describes a portfolio selection method rooted in the classical mean–variance framework that incorporates such asymmetric ... -
Predicting defaults in the automotive credit Industry : an empircial study using machine learning techniques predicting loan defaults
Bøe, Petter Telle (Master thesis, 2020)This master thesis explore the potential of Machine Learning techniques in predicting default of vehicle loan applicants. Usually, banks or other financial institutions utilize the Logistic Regression algorithm to support ... -
Predictive modelling of customer claims across multiple insurance policies : an empirical study of how individual customer insurance data can be used to assess customer risk across multiple insurance products by employing machine learning and advanced ensemble techniques
Høysæter, David; Larsplass, Endre (Master thesis, 2020)In this master thesis, we have analysed how individual insurance customer data can be used to assess customer risk across multiple insurance policies. Our dataset contains 63 variables about the characteristics of each ... -
Recognizing and visualizing copulas : an approach using local Gaussian approximation
Berentsen, Geir Drage; Støve, Bård; Tjøstheim, Dag; Nordbø, Tommy (Working paper;12/12, Working paper, 2012-06)Copulas are much used to model nonlinear and non-Gaussian dependence between stochastic variables. Their functional form is determined by a few parameters, but unlike a dependence measure like the correlation, these ... -
Spot Price Forecasting : Evaluating the Impact of Weather Based Demand Forecasting on Electricity Market Predictions
Sveva, Vebjørn; Sundt, Torolv (Master thesis, 2023)This thesis uses electricity data sourced from Nord Pool and weather data obtained from Norsk Klimaservicesenter, seeking to forecast day-ahead spot prices by leveraging temperature-based demand forecasts. Through this ... -
Stratospheric Influences on Energy Markets : Assessing the Impact of Sudden Stratospheric Warming Events on Nordic Power Trading and Investment Strategies
Hjelmen, Anders; Kongelf, Martin (Master thesis, 2023) -
The heritability of BMI varies across the range of BMI—a heritability curve analysis in a twin cohort
Azzolini, Francesca; Berentsen, Geir Drage; Skaug, Hans Julius; Hjelmborg, Jacob V.B.; Kaprio, Jaakko A. (Peer reviewed; Journal article, 2022)Background: The heritability of traits such as body mass index (BMI), a measure of obesity, is generally estimated using family and twin studies, and increasingly by molecular genetic approaches. These studies generally ... -
Variation in use of Caesarean section in Norway: An application of spatio-temporal Gaussian random fields
Mannseth, Janne; Berentsen, Geir Drage; Skaug, Hans Julius; Lie, Rolv T.; Moster, Dag (Peer reviewed; Journal article, 2021)Aims: Caesarean section (CS) is a medical intervention performed in Norway when a surgical delivery is considered more beneficial than a vaginal. Because deliveries with higher risk are centralized to larger hospitals, use ...