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Stochastic modelling of prey depletion processes

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Affine Variance Swap Curve Models

Damir Filipovic

This paper provides a brief overview of the stochastic modeling of variance swap curves. Focus is on affine factor models. We propose a novel drift parametrization which assures that the components of the state process can be matched with any pre-specified ...

2012

Explicit stabilized integration of stiff determinisitic or stochastic problems

Assyr Abdulle

Explicit stabilized methods for stiff ordinary differential equations have a long history. Proposed in the early 1960s and developed during 40 years for the integration of stiff ordinary differential equations, these methods have recently been extended to ...

Amer Inst Physics2012

Propagation Models for Biochemical Reaction Networks

Maria-Emanuela-Canini Mateescu

In this thesis we investigate different ways of approximating the solution of the chemical master equation (CME). The CME is a system of differential equations that models the stochastic transient behaviour of biochemical reaction networks. It does so by d ...

EPFL2011

Efficient Solution of Ordinary Differential Equations with High-Dimensional Parametrized Uncertainty

Jan Sickmann Hesthaven, Zhen Gao

The important task of evaluating the impact of random parameters on the output of stochastic ordinary differential equations (SODE) can be computationally very demanding, in particular for problems with a high-dimensional parameter space. In this work we c ...

GLOBAL SCIENCE PRESS2011

New variational principles for locating periodic orbits of differential equations

We present new methods for the determination of periodic orbits of general dynamical systems. Iterative algorithms for finding solutions by these methods, for both the exact continuum case, and for approximate discrete representations suitable for numerica ...

2011

Solving the chemical master equation using sliding windows

Maria-Emanuela-Canini Mateescu, Verena Wolf, Rushil Goel

The chemical master equation (CME) is a system of ordinary differential equations that describes the evolution of a network of chemical reactions as a stochastic process. Its solution yields the probability density vector of the system at each point in tim ...

BioMed Central2010

Optimization Problem Coupled with Differential Equations: A Numerical Algorithm Mixing an Interior-Point Method and Event Detection

Jacques Rappaz, Alexandre Caboussat, Christian Landry

The numerical analysis of a dynamic constrained optimization problem is presented. It consists of a global minimization problem that is coupled with a system of ordinary differential equations. The activation and the deactivation of inequality constraints ...

2010

Algebraic Structures of B-series

Gilles Vilmart

B-series are a fundamental tool in practical and theoretical aspects of numerical integrators for ordinary differential equations. A composition law for B-series permits an elegant derivation of order conditions, and a substitution law gives much insight i ...

Springer-Verlag2010

Likelihood-Based Inference for Max-Stable Processes

Simone Padoan

The last decade has seen max-stable processes emerge as a common tool for the statistical modeling of spatial extremes However, their application is complicated due to the unavailability of the multivariate density function and so likehhood-based methods r ...

American Statistical Association2010

Numerical analysis of optimization-constrained differential equations

Chantal Landry

The modeling of a system composed by a gas phase and organic aerosol particles, and its numerical resolution are studied. The gas-aerosol system is modeled by ordinary differential equations coupled with a mixed-constrained optimization problem. This coupl ...

EPFL2009