Англо-русский экономический словарь.
Markov process — In probability theory and statistics, a Markov process, named after the Russian mathematician Andrey Markov, is a time varying random phenomenon for which a specific property (the Markov property) holds. In a common description, a stochastic… … Wikipedia
Continuous-time Markov process — In probability theory, a continuous time Markov process is a stochastic process { X(t) : t ≥ 0 } that satisfies the Markov property and takes values from a set called the state space; it is the continuous time version of a Markov chain. The… … Wikipedia
Semi-Markov process — A continuous time stochastic process is called a semi Markov process or Markov renewal process if the embedded jump chain (the discrete process registering what values the process takes) is a Markov chain, and where the holding times (time… … Wikipedia
Model-based testing — is the application of Model based design for designing and optionally executing the necessary artifacts to perform software testing. Models can be used to represent the desired behavior of the System Under Test (SUT), or to represent the desired… … Wikipedia
Markov chain — A simple two state Markov chain. A Markov chain, named for Andrey Markov, is a mathematical system that undergoes transitions from one state to another, between a finite or countable number of possible states. It is a random process characterized … Wikipedia
Markov property — In probability theory and statistics, the term Markov property refers to the memoryless property of a stochastic process. It was named after the Russian mathematician Andrey Markov.[1] A stochastic process has the Markov property if the… … Wikipedia
Model checking — This article is about checking of models in computer science. For the checking of models in statistics, see regression model validation. In computer science, model checking refers to the following problem: Given a model of a system, test… … Wikipedia
Markov decision process — Markov decision processes (MDPs), named after Andrey Markov, provide a mathematical framework for modeling decision making in situations where outcomes are partly random and partly under the control of a decision maker. MDPs are useful for… … Wikipedia
Model selection — is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre existing set of data is considered. However, the task can also involve the design of experiments such that the data collected is … Wikipedia
Markov model — In probability theory, a Markov model is a stochastic model that assumes the Markov property. Generally, this assumption enables reasoning and computation with the model that would otherwise be intractable. Contents 1 Introduction 2 Markov chain… … Wikipedia
Markov switching multifractal — In financial econometrics, the Markov switching multifractal (MSM) is a model of asset returns that incorporates stochastic volatility components of heterogeneous durations.[1][2] MSM captures the outliers, log memory like volatility persistence… … Wikipedia
