Browsing NTNU Open by Author "Rue, Håvard"
Now showing items 21-35 of 35
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Modelling Correlated Financial Time Series
Ellingsen, Agnar Ask (Master thesis, 2011)Western Bulk is a shipping company that is interested in generating realistic realisations of five different price series; two freight rates, one interest rate and two oil rates. The realisations should keep the internal ... -
Modelling Sub-daily Precipitation Extremes with the Blended Generalised Extreme Value Distribution
Vandeskog, Silius Mortensønn; Martino, Sara; Castro-Camilo, Daniela; Rue, Håvard (Peer reviewed; Journal article, 2022)A new method is proposed for modelling the yearly maxima of sub-daily precipitation, with the aim of producing spatial maps of return level estimates. Yearly precipitation maxima are modelled using a Bayesian hierarchical ... -
Multivariate DCC-GARCH Model: -With Various Error Distributions
Orskaug, Elisabeth (Master thesis, 2009)In this thesis we have studied the DCC-GARCH model with Gaussian, Student's $t$ and skew Student's t-distributed errors. For a basic understanding of the GARCH model, the univariate GARCH and multivariate GARCH models in ... -
Multivariate Distributions Through Pair-Copula Construction: Theory and Applications
Nævestad, Markus (Master thesis, 2009)It is often very difficult, particularly in higher dimensions, to find a good multivariate model that describes both marginal behavior and dependence structure of data efficiently. The copula approach to multivariate models ... -
Multivariate Gaussian Random Fields: The Stochastic Partial Differential Equation approach
Hu, Xiangping (Doctoral Theses at NTNU, 1503-8181; 2013:206, Doctoral thesis, 2013) -
New Doppler-Based Imaging Methods in Echocardiography with Applications in Blood/Tissue Segmentation
Hovda, Sigve (Doktoravhandlinger ved NTNU, 1503-8181; 2007:93, Doctoral thesis, 2007)Part 1: The bandwidth of the ultrasound Doppler signal is proposed as a classification function of blood and tissue signal in transthoracial echocardiography of the left ventricle. The new echocardiographic mode, Bandwidth ... -
Online Learning in Vowpal Wabbit
Øvestad, Thomas (Master thesis, 2015)Online learning methods for sequentially arriving data are growing in popularity. Alternative batch learning methods scale poorly and have memory constraints. The scope of this thesis is to study online learning methods ... -
Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors
Simpson, Daniel; Rue, Håvard; Riebler, Andrea Ingeborg; Martins, Thiago Guerrera; Sørbye, Sigrunn Holbek (Journal article; Peer reviewed, 2017)In this paper, we introduce a new concept for constructing prior distributions. We exploit the natural nested structure inherent to many model components, which defines the model component to be a flexible extension of a ... -
Spatial Modelling and Inference with SPDE-based GMRFs
Fuglstad, Geir-Arne (Master thesis, 2011)In recent years, stochastic partial differential equations (SPDEs) have been shown to provide a usefulway of specifying some classes of Gaussian random fields. The use of an SPDEallows for the construction of a Gaussian ... -
Spatial modelling with R-INLA: A review
Bakka, Haakon; Rue, Håvard; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Bolin, David; Illian, Janine B.; Krainski, Elias Teixeira; Simpson, Daniel; Lindgren, Finn (Journal article; Peer reviewed, 2018)Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically‐sized datasets from scratch is ... -
Statistical Analysis of Space-time Data: New Models and Applications
Krainski, Elias Teixeira (Doctoral theses at NTNU;2018:93, Doctoral thesis, 2018) -
Stochastic Models for Smoothing Splines: A Bayesian Approach
Hellton, Kristoffer Herland (Master thesis, 2011)Flexible data regression is an important tool for capturing complicated trends in data. One approach is penalized smoothing splines, where there are several mainstream methods. A weakness is, however, the quantification ... -
The Expectation Propagation Algorithm for use in Approximate Bayesian Analysis of Latent Gaussian Models
Skar, Christian (Master thesis, 2010)Analyzing latent Gaussian models by using approximate Bayesian inference methods has proven to be a fast and accurate alternative to running time consuming Markov chain Monte Carlo simulations. A crucial part of these ... -
Tree Boosting With XGBoost - Why Does XGBoost Win "Every" Machine Learning Competition?
Nielsen, Didrik (Master thesis, 2016)Tree boosting has empirically proven to be a highly effective approach to predictive modeling. It has shown remarkable results for a vast array of problems. For many years, MART has been the tree boosting method of ... -
You Just Keep on Pushing My Love over the Borderline: A Rejoinder
Simpson, Daniel; Rue, Håvard; Riebler, Andrea Ingeborg; Martins, Thiago Guerrera; Sørbye, Sigrunn Holbek (Journal article; Peer reviewed, 2017)The entire reason that we wrote this paper was to provide a concrete object around which to focus a broader discussion about prior choice and we are extremely grateful to the editorial team at Statistical Science for this ...