Additive models of probabilistic processes

Probabilistic Models for Continuous Ontogenetic Transition Processes

BACKGROUND Probabilistic reaction norms (PRNs) are an extension of the concept of reaction norms, developed to account for stochasticity in ontogenetic transitions. However, logistic regression based PRNs are restricted to discrete time intervals, whereas previously proposed models for continuous transitions are demanding in terms of modelling effort and data needed. METHODOLOGY/PRINCIPAL FIN...

Additive-multiplicative stochastic models of financial mean-reverting processes.

We investigate a generalized stochastic model with the property known as mean reversion, that is, the tendency to relax towards a historical reference level. Besides this property, the dynamics is driven by multiplicative and additive Wiener processes. While the former is modulated by the internal behavior of the system, the latter is purely exogenous. We focus on the stochastic dynamics of vol...

Reactive, Generative and Strati ed Models of Probabilistic Processes

We introduce three models of probabilistic processes, namely, reactive, generative and strati ed. These models are investigated within the context of PCCS, an extension of Milner's SCCS in which each summand of a process summation expression is guarded by a probability and the sum of these probabilities is 1. For each model we present a structural operational semantics of PCCS and a notion of b...

Reactive, Generative, and Stratified Models of Probabilistic Processes

12a. DISTRIBUTION / AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE 13. ABSTRACT (Maximum 200 words) We introduce three models of probabilistic processes, namely, reactive, generative and stratified. These models are investigated within the context of PCCS, an extension of Milner's SCCS in which each summand of a process summation expression is guarded by a probability and the sum of these probab...

Additive Lévy Processes