Examples of using Monte carlo simulation in English and their translations into Hungarian
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Monte Carlo simulation is very popular.
Calibrate a GARCH model and perform Monte Carlo simulation, quantify VaR.
Monte Carlo simulations of the neutron radiation environment on the lunar surface.
Upload date Compulsory courses Monte carlo simulation and applications.
Monte Carlo simulations of radiation environments(cosmic rays& secondary radiations).
A simulation-based analysis which evaluates the models using a Monte Carlo simulation.
In this section, you will see how Monte Carlo simulation can be used as a decision-making tool.
Qualitative expert judgement or relative standard deviation as a% if a Monte Carlo simulation is used.
Use Monte Carlo simulation to analyze uncertainties and ensure sound decision making.
In the next five chapters, you will see examples ofhow you can use Excel to perform Monte Carlo simulations.
A, monte Carlo simulation can be used to generate a range of possible outcomes of a decision made or action taken.
Parameter uncertainty(relative standard deviation as a% if a Monte Carlo simulation is used, otherwise qualitative expert judgement).
Monte Carlo simulation based on a population PK model showed that a dose regimen of 20 mg/kg 8 hourly achieved 60%T>MIC for P.
TIP: Quantitative uncertainty assessments may be calculated for variance associated with the Resource Useand Emissions Profile data using, for example, Monte Carlo simulations.
The Monte Carlo simulation needs fewer constraints and its accuracy increases with the calculation time.
These include basic methods such as partial budgeting, cost-benefit analysis and decision analysis, but also more advanced methodologies such as linear programming,the Markov chain and Monte Carlo simulation.
Monte Carlo Simulation- for modeling uncertainty to help manage business risk and simulate complex systems.
Seco applies that knowledge in combination with sophisticated computer analysis and algorithms, including Monte Carlo simulation techniques that enable automation of cost modelling.
Monte Carlo simulation- enables the user to truly understand and quantify the errors associated with a complete interpretation workflow.
Research research area Study of the structure and thermodynamic propertiesof molecular fluids(bulk phase, electrical double layer, ion channels) with theoretical and Monte Carlo simulation methods.
Monte Carlo simulation of some termophysical properties of two-centre Lennard-Jones fluids along the vapour-liquid equilibrium curve Type of publication: Article.
TIP: Quantitative uncertainty assessments may be calculated for variance associated with the“Resource Useand Emissions Profile” data using, for example, Monte Carlo simulations or other appropriate tools.
Monte Carlo simulation enables us to model situations that present uncertainty and then play them out on a computer thousands of times.
Both in-house and third party strategies undergo thorough back and forward testing,as well as being subjected to Monte Carlo simulations, ensuring that they can react appropriately to a range of possible scenarios.
Monte Carlo simulations supported the use of 500 mg 4-hour infusions every 8 hours in subjects with normal renal function for target pathogens with doripenem MICs 4 mg/l.
In 1962, Kristen Nygaard initiated a project for a simulation language at the Norwegian Computing Center,based on his previous use of the Monte Carlo simulation and his work to conceptualise real-world systems.
The name Monte Carlo simulation comes from the computer simulations performed during the 1930s and 1940s to estimate the probability that the chain reaction needed for an atom bomb to detonate would work successfully.
Note: The name Monte Carlo simulation comes from the computer simulations performed during the 1930s and 1940s to estimate the probability that the chain reaction needed for an atom bomb to detonate would work.
Monte Carlo simulations using pathogen susceptibility results from completed phase 3 trials and population PK data indicated that the%T> MIC target of 35% was achieved in greater than 90% of patients with nosocomial pneumonia, complicated urinary tract infections and complicated intra-abdominal infections, for all degrees of renal function.