Thus, it seems that stochastic process, random process, Markov chain, and Markov process are all the exact same thing... which is a collection of random variables, which are memory-less, …

If a stochastic process with Markov property has a continuous (/discrete) index set with discrete state space, it is a continuous (/discrete) Markov chain. But if the same stochastic process with …

Apr 25, 2017 · A Markov process is basically a stochastic process in which the past history of the process is irrelevant if you know the current system state. In other words, all information about …

Mar 31, 2011 · 3 I was wondering for a Markov process: Is it true that: it is a stationary process, iff its transition probability function is invariant to time-translation (i.e. it is homogeneous) and its …

Jul 3, 2024 · It says that, given the present, the future and the past are independent. In particular, it contains inhomogeneous and homogeneous Markov processes. And sometimes, Markov …

Even stochastic processes arising from Newtonian physics don't have the Markov property, because parts of the state (say, microscopic degrees of freedom) tend not to be observed or …

Aug 14, 2016 · My question is a bit more basic, can the difference between the strong Markov property and the ordinary Markov property be intuited by saying: "the Markov property implies …

Sep 30, 2023 · A Gauss-Markov process is a random process that is both a Gaussian process and a Markov process. What is the difference between them? Are there Gauss-Markov …

Nov 11, 2023 · Explore related questions probability markov-process See similar questions with these tags.

Aug 23, 2015 · Markov process are memoryless in the sense that you only need to know the current state in order to determine statistics about its future. The past does not impact …