Random fields are useful mathematical tools for representing natural phenomena with complex dependence structures in space and/or time. In particular, the Gaussian random field is commonly used due to
Monte Carlo p-values and variances for the hypothesis that the spatial distribution of each vRNA segment is distributed by a homogeneous Poisson process.
The time-dependence of the state variables has been explicitly stated in the transition propensities to differentiate the state variables from parameters. Transitions in the stochastic model.
CTMC model transitions between states and rates. For each time interval, the number of each event that occurs is sampled from a Poisson distribution with the mean of τ times the corresponding transiti
