How can uncertainty in stochastic process models be quantified and communicated? What are sensitivity analysis techniques for stochastic models?

Jun 6, 2018 ... Biological systems can share and collectively process information to yield emergent effects, despite inherent noise in communication. While ... Jul 30, 2018 ... Correlated stochastic process (colored noises) with f − k power spectrum (⁠ 0 < k ≤ 3 ⁠) is characterized by intermediate permutation entropy ... ... process, Positive dependence, Restarting property, Stochastic properties", ... Informational Sciences. https://doi.org/10.1017/S0269964824000111. An ... While classical state-space reconstruction won't work on stochastic processes, such processes do have state-space representations [11], and, in the special ... We present a novel and simple method to numerically calculate Fisher information matrices for stochastic chemical kinetics models. Apr 4, 2006 ... The dynamic features are governed by the information flow, modeled as a stochastic volatility process, and generalize standard ARCH ... The stochastic properties of this process determine long-run learning dynamics. The challenge in establishing convergence results for <λt> stems from the ... Jul 6, 2021 ... Asymmetric information may stem from, e.g., the observation of different stochastic processes or partial knowledge of the structure of the game ... Mar 6, 2020 ... Let Π be a fully connected transition operator for a Markov process on S, where. Π(s, s0) =: πs(s0) is the probability of transitioning from ... Let ξ , η be two random functions (= stationary (generalized) Gaussian random processes). The Gelfand–Pinsker–Yaglom functional (Formula (2.58) from [10]) for ...