Sentence examples for stochastic treatment from inspiring English sources

This paper describes the stochastic treatment of populations, which involves a sequence of so-called product density equations and forms an appropriate framework for handling small systems.

Stochastic treatment of a reactor model is more difficult than a deterministic treatment but can provide more significant information concerning the design parameters.

The stochastic treatment of the model allows the particle description to be readily extended to track more complex particle properties and their transformations.

Consideration of the physics and topology of two-dimensional grain growth suggests that a stochastic treatment is required to determine grain size distribution [Pande CS. Acta Metall 1987 35 2671].

Specifically, expressions are derived to model binary coalescence and breakage with a particular emphasis on the results which are unique to the stochastic treatment, namely the covariances and correlation functions.

In a previous paper, a stochastic treatment of shrinkage led to a kinetic equation, dX t)/ dVex=[1−X t)]2−γ, where X t) is the transformed fraction, Vex is the KJMA extended volume fraction, and γ is a overlap probability between a phantom crystallite and a crystallite.

Phage induction from CEP511 was stochastic, as treatment with inducing agents such as UV or mitomycin C was not necessary.

This procedure was used for the stochastic quantal treatment of tumors with 10 MC samples for uncertainty (j) (for θ, 10 bootstrap samples were resampled with replacement) and 10 MC samples for variability (k).

The full stochastic process treatment of the birth-death-partitioning model is indeed rather complicated, though powerful; and indeed the derivation of common results used in the literature (such as expected heteroplasmy variance arising from Kimura's neutral model) is also complicated.

For example, what is the threshold parameter at which you switch from stochastic to deterministic treatment?

Figure 5(B) shows ROS stable distributions from the average of 100 stochastic simulations for treatment with Drug 1, Drug 2, both drugs or neither drug.