Sökning: "Dynamic Models"

Visar resultat 1 - 5 av 1235 avhandlingar innehållade orden Dynamic Models.

  1. 1. Dynamic Interactions : National Political Parties, Voters and European Integration

    Författare :Johan Hellström; Svante Ersson; Mikko Mattila; Umeå universitet; []
    Nyckelord :SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Euroscepticism; European integration; dynamic representation; panel data; party positions; political parties; public opinion; voters; Political science; Statsvetenskap; statskunskap; political science;

    Sammanfattning : This thesis consists of an introduction and four self-contained papers, designated I-IV, which extend previous research on national political parties and voters in Western Europe. More specifically, the issues addressed are parties’ positions and voters’ opinions on European integration and their dynamic interactions, i.e. LÄS MER

  2. 2. Towards Intelligent Deformable Models for Medical Image Analysis

    Författare :Ghassan Hamarneh; Chalmers University of Technology; []
    Nyckelord :shape modeling; deformable models; principal component analysis; echocardiography; snakes; active shape models; deformable spatio-temporal shape models; medial-based shape profiles; statistical shape variation; spatio-temporal shape analysis; magnetic resonance imaging; hierarchical regional principal component analysis; oral lesions; dynamic programming; segmentation; spring-mass model; shape deformation; optical flow; medical image analysis; artificial life; physics-based modeling; deformable organisms; digital color images; medial axis; active contour models;

    Sammanfattning : Medical imaging continues to permeate the practice of medicine, but automated yet accurate segmentation and labeling of anatomical structures continues to be a major obstacle to computerized medical image analysis (MIA). Deformable models, with its profound roots in estimation theory, optimization, and physics-based dynamical systems, represent a powerful approach to the general problem of medical image segmentation. LÄS MER

  3. 3. Seasonal Adjustment and Dynamic Linear Models

    Författare :Can Tongur; Daniel Thorburn; Sune Karlsson; Stockholms universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; Dynamic linear models; DLM; direct and indirect seasonal adjustment; relative efficiency; Huber loss function; Polls of polls; Wiener process; Swedish elections; Statistics; statistik;

    Sammanfattning : Dynamic Linear Models are a state space model framework based on the Kalman filter. We use this framework to do seasonal adjustments of empirical and artificial data. A simple model and an extended model based on Gibbs sampling are used and the results are compared with the results of a standard seasonal adjustment method. LÄS MER

  4. 4. Variational Inference of Dynamic Factor Models

    Författare :Erik Spånberg; Pär Stockhammar; Gebrenegus Ghilagaber; Sune Karlsson; Stockholms universitet; []
    Nyckelord :NATURAL SCIENCES; NATURVETENSKAP; NATURVETENSKAP; NATURAL SCIENCES; dynamic factor models; variational inference; missing data; nowcasting; expectation maximization; statistik; Statistics;

    Sammanfattning : When we make difficult and crucial decisions, forecasts are powerful and important tools. For that purpose, statistical models can be our most effective aid. Ideally, these models can incorporate large sets of multifaceted data. LÄS MER

  5. 5. Bayesian Sequential Inference for Dynamic Regression Models

    Författare :Parfait Munezero; Mattias Villani; Helga Wagner; Stockholms universitet; []
    Nyckelord :SOCIAL SCIENCES; SAMHÄLLSVETENSKAP; SAMHÄLLSVETENSKAP; SOCIAL SCIENCES; Bayesian sequential inference; Dynamic regression models; Particle filter; Online prediction; Particle smoothing; Linear Bayes; Statistics; statistik;

    Sammanfattning : Many processes evolve over time and statistical models need to be adaptive to change. This thesis proposes flexible models and statistical methods for inference about a data generating process that varies over time. The models considered are quite general dynamic predictive models with parameters linked to a set of covariates via link functions. LÄS MER