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norskInstitutt for matematikk og statistikk: Nye registreringer
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Dirichlet process cluster kernel
(Master thesis; Mastergradsoppgave, 2017-05-16)This thesis aims to apply the Dirichlet process mixture model to the cluster kernel framework. The probabilistic cluster kernel is extended with a Bayesian nonparametric model to avoid critical parameters within the model. The Dirichlet process cluster kernel demonstrate advantages compared to the probabilistic cluster kernel in both classification and clustering. Additionally, the two dimensional ... -
Modelling and analysis of health care services using regression and Markov models
(Master thesis; Mastergradsoppgave, 2017-05-12)Using data from electronic health records this thesis aims to model and analyse health care services provided to adult patients with chronic conditions. Two aspects of health care services, with unique aims, have been examined. The first aspect is related to the aim of investigating factors affecting the patients' self experienced quality of the health care encounters with regards to satisfaction, ... -
Almost affine codes and matroids
(Master thesis; Mastergradsoppgave, 2017-05-15)In this thesis we study various types of block codes, like linear, mutlti-linear, almost affine codes. We also look at how these codes can be described by associated matroids. In addition we look at flags (chains) of codes and see how their behavior can be described using demi-matroids. We also introduce weight polynomials for almost affine codes. -
On the Ewald-Oseen scattering formulation for linear and nonlinear transient wave scattering
(Master thesis; Mastergradsoppgave, 2017-05-16)In this thesis work we develop and apply EOS formulation to three scattering problems: two of them are 1D problems and one is 2D. The first chapter comprises EOS formulations and numerical implementation for 1D scattering problems. Also in this chapter we use different numerical methods to solve test problem and choose the most stable and accurate method for solving of the given 1D problems. ... -
Statistics of Regional Surface Temperatures after 1900: Long-Range versus Short-Range Dependence and Significance of Warming Trends
(Journal article; Tidsskriftartikkel; Peer reviewed, 2016)This paper studies regional climate variability for the time period 1900–2013 using parsimonious stochastic models. Instrumental data records on 5° × 5°, 2° × 2°, and equal-area grids are examined. A long-range dependent (LRD) stochastic process is used as a simplified description of the multitude of response times in the climate system. Fitting a linear trend to the global mean surface temperature ... -
A complex contour based perfectly matched layer applied to a pattern generating model equation.
(Master thesis; Mastergradsoppgave, 2017-02-17)The observable universe consists of several non equilibrium systems that generate spatiotemporal behaviour in the form of various patterns. As the elementary laws of physics and chemistry are unable to explain the pattern forming behaviour of such systems, scientists have turned to desktop experiments and model equations to gain further insight. The model equations that generate numerical solutions ... -
Separable representations of the Poisson, Helmholtz and complex Helmholtz kernels
(Master thesis; Mastergradsoppgave, 2017-02-15)For high accuracy applications of integral operators in higher dimensions the complexity of operation and storage usually grows exponentially with dimensions. One method that has proven successful for handling these difficulties are the separation of the integral kernels as linear combinations of products of one-dimensional kernels, commonly referred to as separation of variables. In this ... -
Spectral characteristics of instrumental and climate model surface temperatures
(Journal article; Tidsskriftartikkel; Peer reviewed, 2016-02-05)The spatiotemporal temperature variability for several gridded instrumental and general circulation climate model data is characterized, contrasting power spectra of local and global temperatures, land and sea temperatures, and temperatures of different regions. There is generally a high degree of agreement between the spectral characteristics of instrumental and climate model data. All but the ... -
Early-warning signals for the onsets of Greenland interstadials and the younger dryas-preboreal transition
(Journal article; Tidsskriftartikkel; Peer reviewed, 2016-05-20)The climate system approaches a tipping point if the prevailing climate state loses stability, making a transition to a different state possible. A result from the theory of randomly driven dynamical systems is that the reduced stability in the vicinity of a tipping point is accompanied by increasing fluctuation levels and longer correlation times (critical slowing down) and can in principle serve ... -
On Data-Independent Properties for Density-Based Dissimilarity Measures in Hybrid Clustering
(Journal article; Tidsskriftartikkel; Peer reviewed, 2016-09-12)Hybrid clustering combines partitional and hierarchical clustering for computational effectiveness and versatility in cluster shape. In such clustering, a dissimilarity measure plays a crucial role in the hierarchical merging. The dissimilarity measure has great impact on the final clustering, and data-independent properties are needed to choose the right dissimilarity measure for the problem ... -
Are there multiple scaling regimes in Holocene temperature records?
(Journal article; Tidsskriftartikkel; Peer reviewed, 2016-04-28)In this article it is discussed how temperature variability on centennial timescales and longer can be described in a simplistic way. By analysing the scaling in late Holocene temperature reconstructions and longer temperature records from Greenland and Antarctic ice cores, we find that the choice of model depends heavily on the data material and timescale one chooses to emphasize. Ignoring data ... -
Comment on "Scaling regimes and linear/nonlinear responses of last millennium climate to volcanic and solar forcing" by S. Lovejoy and C. Varotsos (2016)
(Journal article; Tidsskriftartikkel; Peer reviewed, 2016-07-13)Lovejoy and Varotsos (2016) (L&V) analyse the temperature response to solar, volcanic, and solar plus volcanic forcing in the Zebiak–Cane (ZC) model, and to solar and solar plus volcanic forcing in the Goddard Institute for Space Studies (GISS) E2-R model. By using a simple wavelet filtering technique they conclude that the responses in the ZC model combine subadditively on timescales from 50 to ... -
Late Quaternary temperature variability described as abrupt transitions on a 1/f noise background
(Journal article; Tidsskriftartikkel; Peer reviewed, 2016-03-31)In order to have a scaling description of the climate system that is not inherently non-stationary, the rapid shifts between stadials and interstadials during the last glaciation (the Dansgaard-Oeschger events) cannot be included in the scaling law. The same is true for the shifts between the glacial and interglacial states in the Quaternary climate. When these events are omitted from a scaling ... -
Global warming projections derived from an observation-based minimal model
(Journal article; Tidsskriftartikkel; Peer reviewed, 2016-01-29)A simple conceptual model for the global mean surface temperature (GMST) response to CO2 emissions is presented and analysed. It consists of linear long-memory models for the GMST anomaly response 1T to radiative forcing and the atmospheric CO2-concentration response 1C to emission rate. The responses are connected by the standard logarithmic relation between CO2 concentration and its radiative ... -
Empirical analysis of time-lagged cross-correlations in the Norwegian Stock Market. A discussion of the Efficient Market Hypothesis
(Master thesis; Mastergradsoppgave, 2016-12-15)In this thesis we challenge the existence of weak efficiency in the Norwegian Stock Marked, by analysing time-lagged cross-correlations between log-return series from 811 stocks listed on the Oslo stock exchange and by creating prediction strategies based on the discovered patterns. We limit the strategies to predicting the direction of the movements of the time series only, i.e. either generating ... -
Paris-toppmøtet og spillet om CO2-kvotene
(Chronicle; Kronikk, 2015-11-25) -
Learning similarities between irregularly sampled short multivariate time series from EHRs
(Conference object; Konferansebidrag, 2016-12-04)A large fraction of the Electronic Health Records consists of clinical multivariate time series. Building models for extracting information from these is important for improving the understanding of diseases, patient care and treatment. Such time series are oftentimes particularly challenging since they are characterized by multiple, possibly dependent variables, length variability and irregular ... -
Insulating the Vacuum. Calculating the Casimir force using the boundary integral method with von Neumann boundary conditions
(Master thesis; Mastergradsoppgave, 2016-08-15)In 2012, a new method for calculating the Casimir force between compact objects was developed, expressing the force in terms of a boundary integral equation. The case of perfectly conducting objects with Dirichlet boundary conditions in two dimensions was treated by Isak Kilen. The method was later extended to three dimensions by Karl Øyvind Mikalsen. The contribution of this thesis will be to ... -
Modelling laser-matter interactions using resonant states
(Master thesis; Mastergradsoppgave, 2016-05-12)Studying how light interacts with materials has become important for many technological applications from optical communication to developing of new materials. Therefore scientists have always tried to improve their understanding of these effects. The primary goal has always been to microscopically describe the pertinent processes. This paper provides a brief introduction into the interactions of ... -
High frequency financial time series prediction: machine learning approach
(Master thesis; Mastergradsoppgave, 2016-05-13)Machine learning is a rapidly evolving subfield of computer science. It has enormous amount of applications. One of the application domains is financial data analysis. Machine learning was usually applied for analysis and forecasting of daily financial time series. Availability of high frequency financial data became another challenge with its own specifics and difficulties. Regressors, being a ...
