Steady-state Distribution
In data science, steady-state distribution refers to the long-term behavior of a system that has reached a stable equilibrium. It is a probability distribution that describes the relative frequency of occurrence of each state in the system over time. Steady-state distribution is often used in Markov chain analysis, where it is used to model the behavior of a system that transitions between different states over time. In this context, the steady-state distribution is the distribution of states that the system will tend to occupy over the long run, regardless of its initial state. The steady-state distribution can be calculated by solving a set of linear equations known as the balance equations, which describe the flow of probability between different states in the system.
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