When simulating a model, some random variable inputs may be correlated. One way to introduce this correlation into the simulation is by rank order correlation. In this method a correlation matrix is used to define the correlation structure. The correlation matrix definiteness is important. A correlation matrix must be either positive definite (PD) or positive …
Traditional decision trees are characterized by discrete outcomes. However, Monte Carlo simulation can be combined with a decision tree to have a more rich data set to identify risk. We will show an example of decision tree simulation for an R&D project to see how this works. To simulate a tree, a node’s value (cost …
In this article we are going to discuss using Monte Carlo simulation to perform quantitative risk analysis for project management. The three primary risks to a project are schedule, financial, and technical. Two of these three risks readily lend themselves to be quantified with Monte Carlo simulation: schedule risk and financial risk. If you’re unfamiliar …
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