Monte Carlo Simulation

{
  "id": "MLC-T-ENV-017785",
  "term": "Monte Carlo Simulation",
  "field": "Environment",
  "definitions": [
    "1. A stochastic modeling technique that involves the random selection of sets of input data for use in repetitive model runs. Probability distributions of receiving water quality concentrations are generated as the output of a Monte Carlo simulation.\n\n2. A technique used to estimate the most probable outcomes from a model with uncertain input data and to estimate the validity of the simulated model.\n\n3. A process for making repeated calculations with minor variations of the same mathematical equation, usually with the use of a computer. May be used to integrate variability in the predicted results for a population or the uncertainty of a predicted result. A two-dimensional Monte Carlo simulation may be used to do both. (FDA 2002)\n\n4. A technique used in computer simulations that uses sampling from a random number sequence to simulate characteristics or events or outcomes with multiple possible values. For example, this can be used to represent or model many individual patients in a population with ranges of values for certain health characteristics or outcomes. In some cases, the random components are added to the values of a known input variable for the purpose of determining the effects of fluctuations of this variable on the values of the output variable. (NLM/NICHSR 2004)\n\n5. A technique that can provide a probability function of estimated exposure using distributed values of exposure factors in an exposure scenario. The Monte Carlo simulation involves assigning a joint probability distribution to the input variables (i.e., exposure factors) of an exposure scenario. Next, a large number of independent samples from the assigned joint distribution are taken and the corresponding outputs calculated. This is accomplished by repeated computer runs (i.e., ≥ 1,000 iterations), using random numbers to assign values to the exposure factors. The simulated output represents a sample from the true output distribution. Methods of statistical inference are used to estimate, from the exposure output sample, some parameters of the exposure distribution, such as percentiles, mean, variance, and confidence intervals. The Monte Carlo simulation can also be used to test the effect that an input parameter has on the output distribution. (REAP 1995)\n\n6. A technique for characterizing the uncertainty and variability in exposure (or risk) estimates by repeatedly sampling the probability distributions of the exposure (or risk) equation inputs and using these inputs to calculate a range of exposure (or risk) values. [U.S. EPA Risk Assessment Guidance for Superfund (RAGS) Volume III - Part A (https://www.epa.gov/risk/risk-assessment-guidance-superfund-rags-volume-iii-part)]\n\n7. A technique for characterizing the uncertainty and variability in exposure (or risk) estimates by repeatedly sampling the probability distributions of the exposure (or risk) equation inputs and using these inputs to calculate a range of exposure (or risk) values.",
    "1. A process for making repeated calculations with minor variations of the same mathematical equation, usually with the use of a computer. May be used to integrate variability in the predicted results for a population or the uncertainty of a predicted result. A two-dimensional Monte Carlo simulation may be used to do both.\n\n2. A technique used in computer simulations that uses sampling from a random number sequence to simulate characteristics or events or outcomes with multiple possible values. For example, this can be used to represent or model many individual patients in a population with ranges of values for certain health characteristics or outcomes. In some cases, the random components are added to the values of a known input variable for the purpose of determining the effects of fluctuations of this variable on the values of the output variable."
  ],
  "subject": [
    "Chemicals, toxics and pesticides",
    "Health and safety"
  ],
  "references": [
    "Sediment Total Maximum Daily Loads (TMDLs) Glossary",
    "Glossary: Study of the Potential Impacts of Hydraulic Fracturing on Drinking Water Resources; EPA Study of the Potential Impacts of Hydraulic Fracturing on Drinking Water Resources: Progress Report at http://www.epa.gov/hfstudy/pdfs/hf-report20121214.pdf",
    "Thesaurus of Terms Used in Microbial Risk Assessment",
    "EPA ExpoBox Terminology",
    "U.S. EPA Risk Assessment Guidance for Superfund (RAGS) Volume III - Part A (https://www.epa.gov/risk/risk-assessment-guidance-superfund-rags-volume-iii-part)",
    "FDA 2002",
    "NLM/NICHSR 2004"
  ],
  "url": "https://mlchart.com/terminology/environment/monte-carlo-simulation/"
}