Browsing Institutt for matematiske fag by Subject "Fysikk og matematikk, Industriell matematikk"
Now showing items 21-40 of 164
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An algorithmic Framework for Multiresolution based non-parametric Regression
(Master thesis, 2017)We study a method to solve non-parametric regression problems in one and two dimensions with statistical multiresolution estimation. We present the non-parametric regression problem, then introduce the multiresolution norm ... -
An Investigation Into Braess' Paradox and Selfish Routing in Traffic Flow - Solving the non-linear traffic program with linear cost functions on traffic networks
(Master thesis, 2014)The aim of this master thesis was to investigate Braess' Paradox in traffic flow and to look at the effect of selfish routing in optimization of flow distribution on traffic networks. Braess' Paradox is a well known ... -
An Optical Flow based Method for the Segmentation of Image Sequences
(Master thesis, 2017)The segmentation of motion in an image sequence is an important task in many computer vision applications. This thesis presents the theory and numerical algorithm for the detection of object boundaries of moving objects ... -
Analyse av risikoen for rente -og aksjeporteføljer med LIBOR Market Modellen
(Master thesis, 2015)Dette arbeidet fil først presentere matematikken og teorien bak rente og aksjeopsjoner, og vise noen vanlige modeller. Vi utlederde stokastiske ligningene i LIBOR Market Modellen, og viser hvordan derivater som caps, floor ... -
Analysis of Bivariate Extreme Values
(Master thesis, 2015)Results show that there is high agreement between the distribution of the bivariate ACER functions and the distribution of the copula models with ACER marginals for all time series. The distribution of the copula models ... -
Analysis of Censored Data from Split-Plot Design
(Master thesis, 2015)In reliability theory, there are often data missing due to censoring. Such incomplete datasets are usually difficult to analyse. The exact value of the censored data is not known, but some information exists. That is, the ... -
Anisotropic Total Variation Based Image Restoration Using Graph Cuts
(Master thesis, 2015)In this thesis we consider a particular kind of edge-enhancing image restoration method based on total variation. We want to address the fact that the total variation method in some cases leads to contrast loss in thin ... -
Application of a Bayesian Choice Model on Monthly Client Data - at SpareBank 1 SMN
(Master thesis, 2015)This paper applies a Bayesian Dynamic Choice model on monthly collected client data at SpareBank 1 SMN in order to examine the rate at which they enter or leave Life- and Danage-insurance. The main goal of the paper is ... -
Application of Nek5000 to dispersion simulations
(Master thesis, 2016)Simulations of turbulent flow and gas dispersion are performed using Nek5000, with and without a subgrid-scale model. The results are compared with data from wind- tunnel experiments and previously performed simulations ... -
Applications of Paillier s Cryptosystem.
(Master thesis, 2016)Applications of Paillier s crypto system to electronic voting. -
Approximate marginal inference in binary Markov random fields using a mean squared error energy approximation and the junction tree algorithm
(Master thesis, 2016)In this thesis, we use a mean squared error energy approximation for edge deletion in order to make performing inference in Markov random fields using the junction tree algorithm tractable, and by that develop an approximate ... -
Backtesting counterparty credit exposure based on the Heath, Jarrow and Morton framework for simulation of interest rates
(Master thesis, 2018)In this thesis a framework for backtesting counterparty credit exposure is developed and implemented. Using the Heath, Jarrow and Morton model for simulation of interest rates, separate models are implemented for risk-neutral ... -
Bayesian Gaussian Inversion of Time-Lapse Seismic AVO Data
(Master thesis, 2017)The goal of this study is to characterize an oil reservoir along a depth profile at two different points in time, based on seismic AVO data gathered at these times. We apply Bayesian methodology to the inversion problem. ... -
Bayesian Model Averaging Using Varying Coefficient Regression and Climatology Cumulative Probability Regression - A Case Study of Postprocessing Hydrological Ensembles from Osali
(Master thesis, 2017)Bayesian Model Averaging Using Varying Coefficient Regression and Climatology Cumulative Probability Regression. -
Beregninger av Optimeringsproblemer i Statistisk Læring med TensorFlow
(Master thesis, 2016)Modeller i statistisk læring, spesielt Nevrale Nettverk, har blitt anvendt med stor suksess på en rekke problemer i Kunstig Intelligens. Denne oppgaven beskriver og demonstrerer TensorFlow, som er en softwarepakke laget ... -
Changepoint model selection in Gaussian data by maximization of approximate Bayes Factors with the Pruned Exact Linear Time algorithm
(Master thesis, 2018)In this thesis we consider the changepoint detection in independently distributed Gaussian data. Detection of multiple changepoints in a data set is treated as a model selection problem where the model complexity is ... -
CO2 Sequestration - a Near-Well Study
(Master thesis, 2017)Carbon Capture and Storage (CCS) has been proposed as a promising and necessary tool in strategies for mitigating the effects of anthropogenic climate change. Deep geological formations, like saline aquifers, are pointed ... -
Colourful Cohomology
(Master thesis, 2017)The thesis starts out by explaining connections between graph theory, category theory and homology. Thereafter, the very abstract is translated into geometrical concepts, simplicial cohomology is especially derived. ... -
Comparing the ACER and POT MCMC Extreme Value Statistics Methods Through Analysis of Commodities Data
(Master thesis, 2016)The Average Conditional Exceedance Rate and Peak Over Threshold Markov Chain Monte Carlo are two extreme value statistical methods, compared in this work. They are tested for both extrapolations and prediction intervals. ... -
Computationally efficient Bayesian approximation of fractional Gaussian noise using AR1 processes
(Master thesis, 2016)The goal of this thesis is to explore a way of performing efficient Bayesian inference of fractional Gaussian noise series using the R-INLA framework. Finding the MLE of the Hurst exponent and the innovation variance of ...