Markov chain Monte Carlo

{
  "id": "MLC-T-ENV-016603",
  "term": "Markov chain Monte Carlo",
  "field": "Environment",
  "definition": "1. A type of quantitative modeling that involves a specified set of mutually exclusive and exhaustive states (e.g., of a given health status), and for which there are transition probabilities of moving from one state to another (including of remaining in the same state). Typically, states have a uniform time period, and transition probabilities remain constant over time.\n\n2. A general method of sampling arbitrary highly-dimensional probability distributions by taking a random walk through configuration space. One changes the state of the system randomly according to a fixed transition rule, thus generating a random walk through state space, s0,s1,s2, ... . The definition of a Markov process is that the next step is chosen from a probability distribution that depends only on the present position. This makes it very easy to describe mathematically. The process is often called the drunkard’s walk (statistics). (FAO/WHO 2003b)\n\n3. A type of quantitative modeling that involves a specified set of mutually exclusive and exhaustive states (e.g., of a given health status), and for which there are transition probabilities of moving from one state to another (including of remaining in the same state). Typically, states have a uniform time period, and transition probabilities remain constant over time. (NLM/NICHSR 2004)",
  "subject": "Health and safety",
  "references": [
    "NLM/NICHSR 2004",
    "EPA Thesaurus of Terms Used in Microbial Risk Assessment: 5.9 Modeling, Statistics, and Math Terms at http://water.epa.gov/scitech/swguidance/standards/criteria/health/microbial/T59.cfm"
  ],
  "url": "https://mlchart.com/terminology/environment/markov-chain-monte-carlo/"
}