What are some applications of continuous-time Markov chains? What is a Poisson process?

... informational and statistical characterization of the classical stochastic processes that result from that interaction.As a classical observer uses a ... ), Arbitrage, Credit and Informational Risks, (pp. 53-86). Singapore: World ... Stochastic Processes and their Applications, 129(4), 1229-1258. [More ... Admissible Data Processes. In applying the competitive message process to stochastic environments, we have thus far required uninformed agents to use the ... If the stochastic process representing the belief over f is sufficiently regular, then Equation (1) can be approximated arbitrarily well with finitely many ... Nov 30, 2020 ... It is initially unknown what the parameter process corresponds to biologically, hence the moniker 'hidden' state. Nevertheless, the information ... In particular, if we partition a set of stochastic processes into groups whose sums must be forecast independently, then the statistical properties of each ... We present a novel and simple method to numerically calculate Fisher information matrices for stochastic chemical kinetics models. Jan 20, 2022 ... ... stochastic processes, and information dynamics approaches. Our analysis revealed novel relationships between these metrics, which allowed us ... Gaussian stochastic process with mean. Er|θ. [∆ϑ(r)] = 1 n !i f [bi + #i(θ)] ... Information-theoretic asymptotics of Bayes methods. IEEE Trans- actions ... Jul 30, 2018 ... Correlated stochastic process (colored noises) with f − k power spectrum (⁠ 0 < k ≤ 3 ⁠) is characterized by intermediate permutation entropy ...