Browsing NTNU Open by Author "Tjelmeland, Håkon"
Now showing items 1-20 of 47
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A Bayesian model for lithology/fluid class prediction using a Markov mesh prior fitted from a training image
Tjelmeland, Håkon; Luo, Xin; Fjeldstad, Torstein Mæland (Journal article; Peer reviewed, 2019)We consider a Bayesian model for inversion of observed amplitude variation with offset data into lithology/fluid classes, and study in particular how the choice of prior distribution for the lithology/fluid classes influences ... -
A Bayesian model for the dependence structure in binary Markov random fields.
Frøysa, Cecilie Drabløs (Master thesis, 2014)In this thesis a reversible jump Markov chain Monte Carlo (MCMC) method for simulation of the graph structure of a binary Markov random field (MRF) is presented. The reversible jump MCMC method allows for simulation of ... -
A multiple-try Metropolis-Hastings algorithm with a tailored number of proposals
Heggstad, Steinbru Hilde (Master thesis, 2019)Oppgaven presenterer en multiple-try Metropolis Hastings algoritme, som utvider målfordelingen til å sample en rettet asyklisk graf med et sett av noder og rettede kanter. Hver node er assosiert med en verdi som potensielt ... -
A multiple-try Metropolis–Hastings algorithm with tailored proposals
Luo, Xin; Tjelmeland, Håkon (Journal article; Peer reviewed, 2019)We present a new multiple-try Metropolis–Hastings algorithm designed to be especially beneficial when a tailored proposal distribution is available. The algorithm is based on a given acyclic graph G, where one of the nodes ... -
An empirical study of the maximum pseudo-likelihood for discrete Markov random fields.
Fauske, Johannes (Master thesis, 2009)In this text we will look at two parameter estimation methods for Markov random fields on a lattice. They are maximum pseudo-likelihood estimation and maximum general pseudo-likelihood estimation, which we abbreviate ... -
Approximate marginal inference in binary Markov random fields using a mean squared error energy approximation and the junction tree algorithm
Wiig, Trygve Bertelsen (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 ... -
Approximate recursive algorithm for finding MAP of binary Markov random fields
Altaye, Endale Berhane (Master thesis, 2010)The purpose of this study was to develop a recursive algorithm for computing a maximum a posteriori (MAP) estimate of a binary Markov random field (MRF) by using the MAP-MRF framework. We also discuss how to include an ... -
Approximate recursive calculations of discrete Markov random fields
Arnesen, Petter (Master thesis, 2010)In this thesis we present an approximate recursive algorithm for calculations of discrete Markov random fields defined on graphs. We write the probability distribution of a Markov random field as a function of interaction ... -
Assosiasjon mellom posisjonsinformasjon og peilinger fra en satellitt over nordområdene
Birkenes, Tor Inge (Master thesis, 2012)Forsvarets forskningsinstitutt (FFI) har ønske om å utvide eksisterende satellittovervåking av nordområdene fra kun posisjonsinformasjon mottatt via ''Automatisk indentifikasjonssystem'' (AIS) til å også inkludere ... -
Automatic Parametrisation and Block pseudo Likelihood Estimation for binary Markov random Fields
Toftaker, Håkon (Master thesis, 2008)Discrete Markov random fields play an important role in spatial statistics, and are applied in many different areas. Models which consider only pairwise interaction between sites such as the Ising model often perform well ... -
Bayesian 4D inversion: integrating time-shift information
Sande, Stian (Master thesis, 2006)A new inversion method for time-lapse seismic data is developed. The method is based on the 3-dimensional spatially coupled AVO inversion in the Fourier domain, describedin Buland et al. (2003b). Further, a technique for ... -
Bayesian ensemble filtering for a model with categorical and continuous variables
Brady, Vilde (Master thesis, 2021)Det Bayesianske ensemble filteret er presentert i Loe og Tjelmeland (2021). Det er en generalisering av det tradisjonelle ensemble Kalmanfilteret (EnKF) og er en løsning på filtreringsproblemet i statistikk. Ensemble ... -
Bayesian inference for Markov mesh models – applied to inversion of seismic data
Luo, Xin (Doctoral theses at NTNU;2019:16, Doctoral thesis, 2018)To characterize a petroleum reservoir there are different types of data available, for example, seismic data and observations in wells. In this scenario, it is natural to adopt a Bayesian framework to incorporate observations ... -
Data Analysis of Magnetotelluric Survey Data
Bratteland, Tarjei (Master thesis, 2014)We study data from marine magnetotelluric (MT) surveys. In MT surveys the objective is to study the distribution of resistivity in the Earth's subsurface, and the quantity of interest is the impedance Z(ω). The impedance ... -
Efficient Calculation of Optimal Decisions in Graphical Models
Lilleborge, Marie (Master thesis, 2012)We present a method for finding the optimal decision on Random Variables in a graphical model. Upper and lower bounds on the exact value for each decision are used to reduce the complexity of the algorithm, while we still ... -
En empirisk studie av FRAME-modellens egenskaper
Larsen, Jens Helge Grutle (Master thesis, 2009)I denne rapporten beskriver vi en statistisk modell som fanger opp teksturer i et bilde og overfører disse til et annet bilde. Vi modellerer bilder som markovfelt, og beskriver filtre som vi bruker til å fange opp forskjellen ... -
Ensemble updating for a state-space model with categorical variables
Loe, Margrethe Kvale (Doctoral theses at NTNU;2021:303, Doctoral thesis, 2021) -
Ensemble updating of binary state vectors by maximising the expected number of unchanged components
Loe, Margrethe Kvale; Tjelmeland, Håkon (Peer reviewed; Journal article, 2020)The main challenge in ensemble-based filtering methods is the updating of a prior ensemble to a posterior ensemble. In the ensemble Kalman filter (EnKF), a linear-Gaussian model is introduced to overcome this issue, and ... -
Hierarchical Bayesian modeling of wind related transmission line failures
Wankel, Norunn Ahdell (Master thesis, 2019)Elektrisitet er viktig i dagens samfunn og noe vi nærmest tar for gitt at alltid skal være tilgjengelig. Det kan være mange grunner til at deler av kraftsystemet feiler, og vær er en av dem. I denne masteroppgaven formulerer ... -
Hierarchical ensemble Kalman filter formulated with sparse matrices
Gryvill, Håkon (Master thesis, 2020)Hierarkisk ensemble Kalmanfilter (HEnKF), introdusert i Omre og Myrseth (2010), er en utvidelse av ensemble Kalmanfilter (EnKF). Ved å ilegge en hierarkisk modell på state space-variablene har HEnKF vist å gi mer robuste ...