As large-scale discrete-event stochastic simulation becomes a tool that is used routinely for the design and analysis of stochastic systems, the need for input-modeling support with the ability to ...

Stochastic modelling of reaction–diffusion systems has emerged as a crucial framework for understanding the complex interplay between chemical reactions and molecular diffusion in biological ...

Topics Discrete event simulation modeling Design and analysis of simulation experiments Simulation optimization Variance reduction & rare event simulation MCMC, steady-state simulation, and exact ...

In this paper we present an exact maximum likelihood treatment for the estimation of a Stochastic Volatility in Mean (SVM) model based on Monte Carlo simulation methods. The SVM model incorporates the ...

This paper documents the specification of a model that was constructed to assess debt sustainability in emerging market economies. Key features of the model include external and fiscal sectors, which ...

This project aims at developing mathematical statistics and probability theory to provide methodologies for modeling and analysis of complex random systems. Statistical methods enable analysis of ...

This course provides the skills needed to examine and apply modern statistical and machine learning methods to significant real-world computational issues in finance, risk management, and insurance.

The special case of simulation of non-Gaussian vector fields modeling material properties is examined, mainly from the point of view of certain simplifying assumptions that can be made for such random ...

This paper presents and estimates a small open economy dynamic stochastic general-equilibrium model (DSGE) for the Jordanian economy. The model features nominal and real rigidities, imperfect ...