If Y has the Markov property, then it is a Markovian representation of X. An example of a non-Markovian process with a Markovian representation is an autoregressive time series of order …

Mar 1, 2026 · A stochastic process is called Markovian (after the Russian mathematician Andrey Andreyevich Markov) if at any time t the conditional probability of an arbitrary future event given the …

Dec 11, 2025 · The term “Markovian” describes a system or process where the likelihood of what happens next depends exclusively on its current condition, completely disregarding the …

The meaning of MARKOVIAN is of, relating to, or resembling a Markov process or Markov chain especially by having probabilities defined in terms of transition from the possible existing states to …

A Markovian process is defined as a random sequential set of events where the likelihood of the next event can be predicted solely based on the last event, without requiring information from prior events.

Markovian and non-Markovian processes and Master Equation. A Markov process assumes that the next state of a process only depends on the present state and not the past states.

Mar 24, 2021 · A Markovian process is a state-transition process which can be represented by a state-transition graph showing the states of the system and the transitions between these states.

The main characteristic of a Markovian process is the "memoryless" property, meaning the probability of transitioning to any particular state is based solely on the current state and time spent in the …

Jul 1, 2015 · Yet it’s fair to say that everything is Markovian and nothing is Markovian – and we need to understand this. If you’re new to the business, a quick word on what “Markovian” means.

Mar 2, 2026 · MOSAIC unifies heterogeneous rates, dynamic interaction preferences, and both Markovian and non-Markovian waiting-time distributions within a single stochastic formalism, while …