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Showing result 1 - 5 of 632 swedish dissertations matching the above criteria.

2. 1. Modelling animal populations

   Author : Åke Brännström; Umeå universitet; []
   Keywords : population model; stochastic population model; population dynamics; discrete time model; Beverton-Holt model; Skellam model; Hassell model; Ricker model; first principles; coupled map lattice; CML; area integral; square function; Mathematics; matematik;

   Abstract : This thesis consists of four papers, three papers about modelling animal populations and one paper about an area integral estimate for solutions of partial differential equations on non-smooth domains. The papers are: I. Å. Brännström, Single species population models from first principles. READ MORE

4. 2. Improved pharmacometric model building techniques

   Author : Radojka Savic; Mats Karlsson; Siv Jönsson; Matt Hutmacher; Uppsala universitet; []
   Keywords : Model building; Absorption model; Transit compartment model; Nonparametric method; Extended grid method; Semiparametric; Distribution transformation; Shrinkage; Model diagnostics;

   Abstract : Pharmacometric modelling is an increasingly used method for analysing the outcome from clinical trials in drug development. The model building process is complex and involves testing, evaluating and diagnosing a range of plausible models aiming to make an adequate inference from the observed data and predictions for future studies and therapy. READ MORE

5. 3. Stochastic model updating and model selection with application to structural dynamics

   Author : Majid Khorsand Vakilzadeh; Chalmers tekniska högskola; []
   Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Finite element model; Bayesian model selection; Bayesian model updating; stochastic simulation; Bootstrapping; Subspace system identification; Uncertainty quantification;

   Abstract : Uncertainty induced by our incomplete state of knowledge about engineering systems and their surrounding environment give rise to challenging problems in the process of building predictive models for the system behavior. One such challenge is the model selection problem, which arises due to the existence of invariably multiple candidate models with different mathematical forms to represent the system behavior, and so there is a need to assess their plausibility based on experimental data. READ MORE

6. 4. Graphical representations of Ising and Potts models : Stochastic geometry of the quantum Ising model and the space-time Potts model

   Author : Jakob Erik Björnberg; Anders Björner; Jeffrey Steif; KTH; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; Quantum Ising model; Ising model; Potts model; random-cluster model; random-current representation; random-parity representation; differential inequality; phase transition; Discrete mathematics; Diskret matematik;

   Abstract : HTML clipboard Statistical physics seeks to explain macroscopic properties of matter in terms of microscopic interactions. Of particular interest is the phenomenon of phase transition: the sudden changes in macroscopic properties as external conditions are varied. READ MORE

7. 5. Contributions to Numerical Solution of Stochastic Differential Equations

   Author : Anders Muszta; Göteborgs universitet; []
   Keywords : NATURVETENSKAP; NATURAL SCIENCES; adaptive method; change of time; CIR model; CKLS model; convergence order; Euler method; heavy-tailed SDE; hyperbolic SDE; geometric integration; global Lipschitz condition; Levy process; Lie group method; local Lipschitz condition; local martingales; mean reversion; Milstein method; numerical method; semimartingale; stochastic differential equation; stochastic Taylor expansion; strong approximation; symplectic integration; volatility induced stationarity; waveform relaxation; volatility induced stationarity;

   Abstract : This thesis consists of four papers: Paper I is an overview of recent techniques in strong numerical solutions of stochastic differential equations, driven by Wiener processes, that have appeared the last then 10 years, or so. Paper II studies theoretical and numerical aspects of stochastic differential equations with so called volatility induced stationarity. READ MORE