Bubble dynamic morphology was modelled with stochastic techniques and the output from this was used in the kinetic model to predict dispersion in bubble displacement with time.
The time series can be modelled with stochastic time series models such as Arima models or state space models.
Spread of BVDV through the herd was modeled with a stochastic SIR model.
Two positive molecular resist architectures are modeled with a stochastic lithography simulator and their LER behavior is quantified.
For computational simplicity, the cytosol is treated as a well-mixed solution and modeled with the stochastic simulation algorithm of Gillespie [39].
With the theory developed above, additional modeling efforts are needed to combine this model with stochastic features of linear statistical and landscape models for parameter estimation, genetic network construction and genotype-phenotype prediction in breeding populations.
Figure 7 Phase space portrait for the MSIRS endemic model with stochastic perturbations.
We consider nonlinear mixed-effects ODE model with stochastic approximation EM algorithm to overcome these difficulties.
We propose a state space mixed model with stochastic volatility for ordinal-response time series data.
In this paper, we consider a perturbed compound Poisson risk model with stochastic premiums and constant interest force.
