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Browsing Department of Mathematics by Subject "753299"

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Now showing items 1-20 of 58

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    • A Comparison of the local Gaussian correlation and the local dependence function 

      Brokstad, Christopher James (Master thesis, 2022-06-01)
      Correlation is a method to measure the relation between two or more variables. In this thesis, a method of measuring correlation and a method of measuring dependence are used. These two methods, are the local Gaussian ...
    • A Dimensionality Reducing Extension of Bayesian Relevance Learning 

      Heimsæter, Sandra Vervik (Master thesis, 2021-02-11)
      When modeling with big data and high dimensional data, the ability to extract the most important information from the data set and avoid overfitting is crucial. However, by using well developed sparse methods, we can ...
    • Analysis of left truncated data with an application to insurance data 

      Berentsen, Geir Drage (Master thesis, 2009-06-02)
      This thesis discusses different ways of analysing left truncated data when the lower bound itself is a stochastic variable. We will consider the possible dependence between the variable of interest and the truncating ...
    • Analysis of the probability of default in peer-to-peer lending. Application of different classification techniques. 

      Evjen, Endre Kvåle (Master thesis, 2018-12-22)
      In this thesis, peer-to-peer lending is explored and analyzed with the objective of fitting a model to accurately predict if borrowers default on their loans or not. The foundation for the thesis is a dataset from LendingClub, ...
    • APARCH Models Estimated by Support Vector Regression 

      Waagbø, Arne Ladstein (Master thesis, 2021-06-01)
      This thesis presents a comprehensive study of asymmetric power autoregressive conditional heteroschedasticity (APARCH) models for modelling volatility in financial return data. The goal is to estimate and forecast volatility ...
    • Chain Ladder Metoden og Mack's Modell sammenlignet med andre Poissonbaserte modeller 

      Sagosen, Monica (Master thesis, 2010-05-30)
      Ønsker å se på reservering til fremtidige krav. Vil først og fremst se på Chain Ladder metoden og Mack sin modell. Vil så forsøke å simulere data etter en modell som passer med Mack sine tre antakelser, den sammensatte ...
    • Close-Kin Mark-Recapture Models 

      Førland, Brage (Master thesis, 2019-07-09)
      Close-Kin Mark-Recapture (CKMR) is a recent extension of the ordinary mark–recapture methods used to estimate animal abundance and other population parameters. Where ordinary mark–recapture only consider the subsequent ...
    • Commutability of Control Materials - Statistical Methods of Evaluation. 

      Fauskanger, Pernille Kjeilen (Master thesis, 2020-12-15)
    • Comparing Maximum Likelihood and Generalized Method of Moments in Short Term Interest Rate Models 

      Hanevik, Severin (Master thesis, 2016-02-01)
      In this thesis we will look at some different continuous models for predicting the short term interest rate, and focus on the method of parameter estimation in such models. A particular focus will be placed on the method ...
    • Copulas and Local Gaussian Correlation 

      Nordbø, Tommy Neverdahl (Master thesis, 2012-05-30)
      We are looking at copula models and dependence measures. Especially the recently developed local dependence measure called local Gaussian correlation (LGC) is presented, and its connection with the copula theory is explored. ...
    • DCC-GARCH modeller med ulike avhengighetsstrukturer 

      Aardal, Helene (Master thesis, 2013-03-14)
      Hovedfokuset i denne oppgaven er å finne gode metoder for modellering av volatilitet og avhengighetsstruktur i finansielle porteføljer. En spesifikk multivariat GARCH modell, Dynamic Conditional Correlation (DCC-) GARCH, ...
    • Deep learning-based cross-sensor super resolution of satellite images 

      Nordberg, Øystein Helle (Master thesis, 2021-11-22)
      Subtitle: Multispectral-to-panchromatic single-image super resolution of GeoEye-1 satellite images using an ESRGAN deep learning model trained exclusively on WorldView-2 images. Abstract: Today, easy and abundant access ...
    • Discrete hidden Markov modelswith application to stock tradingalgorithms 

      Hansen, Andreas (Master thesis, 2021-01-31)
    • An Exploratory Analysis of Multi-Class Uncertainty Approximation in Bayesian Convolutional Neural Networks 

      Murray, Sean Meling (Master thesis, 2018-11-22)
      Neural networks are an important and powerful family of models, but they have lacked practical ways of estimating predictive uncertainty. Recently, researchers from the Bayesian machine learning community developed a ...
    • GAMLSS-modeller i bilforsikring 

      Røyrane-Løtvedt, Hallvard (Master thesis, 2012-06-01)
      I denne oppgaven tester jeg ulike modeller for prediksjon av total skadeutbetaling fra forsikringsselskap til forsikringstaker i et poliseår. Modellene som testes hører til rammeverket Generalized Additive Models for ...
    • Hidden Markov and Hidden Semi-Markov models on Financial Timeseries 

      Eilertsen, Emil Lund (Master thesis, 2020-09-11)
    • Hierarchical Bayesian Survival Analysis of Age-Specific Data From Birds' Nests 

      Willgohs, Niejing (Master thesis, 2010-11-19)
      In this thesis, I first present the grassland birds data from Wells(2007) which is used by several different methods of estimating the nest survival rates. The hierarchical Bayesian method from Cao(2009) then is introduced ...
    • Høyfrekvens finans og markedets mikrostruktur på Oslo Børs 

      Danielsen, Arne (Master thesis, 2009-09-09)
      Høyfrekvens finans, som er tema for denne oppgaven, tar for seg studiet av høyfrekvente finansielle data. I denne oppgaven har vi sett på data med den høyest mulige frekvensen, nemlig data fra hver eneste handel. De ...
    • Inferring CRCs progression dynamic with HyperTraPS 

      Chen, Hsiu Jane (Master thesis, 2021-07-07)
    • Interest rate models in Solvency II 

      Sivertsen, Kristine (Master thesis, 2016-11-21)
      The best estimate of liabilities is important in the Solvency II framework. The best estimate of liabilities should be probability weighted average of future cash flows discounted to its present value. Life insurance ...

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