Cellular dynamics are intrinsically noisy, so mechanistic models must incorporate stochasticity if they are to adequately model experimental observations. As well as intrinsic stochasticity in gene ...

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): ...

Simulation research derives new methods for the design, analysis, and optimization of simulation experiments. Research on stochastic models develops and analyzes models of systems with random behavior ...

For many stochastic models, it is difficult to make inference about the model parameters because it is impossible to write down a tractable likelihood given the observed data. A common solution is ...

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 course is available on the MSc in Applicable Mathematics, MSc in Econometrics and Mathematical Economics, MSc in Financial Mathematics, MSc in Operations Research & Analytics, MSc in Quantitative ...

Stochastic volatility models are increasingly important in practical derivatives pricing applications, yet relatively little work has been undertaken in the development of practical Monte Carlo ...

Graduate standing, or permission of instructor. Statistics, and real analysis at the undergraduate engineering or mathematics level; graduate level probability and stochastic processes (IEMS 460-1); ...