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 dynamical systems arise in many scientific fields, such as asset prices in financial markets, neural activity in ...

This is a preview. Log in through your library . Abstract (1) Spatial processes in an acarine predator-prey system were simulated by a stochastic population model. (2) The model describes interactions ...

Erkyihun S.T., E Zagona, B. Rajagopalan, (2017). “Wavelet and Hidden Markov-Based Stochastic Simulation Methods Comparison on Colorado River Streamflow,” Journal of Hydrologic Engineering 2017, 22(9): ...

We present a stochastic simulation model for estimating forward-looking corporate probability of default and loss given default. We formulate the model in a discrete time frame, apply ...

Statistics, and real analysis at the undergraduate engineering or mathematics level; graduate level probability and stochastic processes (IEMS 460-1); computer programming in Python; graduate standing ...

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 ...

Peter Friz, Paolo Pigato and Jonathan Seibel propose a modification of a given stochastic volatility model ‘backbone’ capable of producing extreme short-dated implied skews, without adding jumps or ...