Monte Carlo simulation is a statistical methodology used to mannequin and analyze the habits of complicated programs by producing random samples from an enter distribution and operating these samples via a course of or mannequin to see how the output adjustments. It’s typically used to research uncertainty in a course of or mannequin, in addition to to foretell future outcomes or chances of sure occasions occurring.
In a Monte Carlo simulation, you begin by defining the inputs to the simulation, which are sometimes represented by chance distributions. These chance distributions describe the vary of doable values that every enter can take and the probability of every worth occurring. As soon as the enter distributions have been outlined, you’ll be able to generate numerous random samples from these distributions and use these samples as inputs to your course of or mannequin. The output of the method or mannequin is then analyzed to see the way it adjustments based mostly on the completely different enter values. This course of is repeated many instances to generate numerous output values, which may then be analyzed to grasp the habits of the system below completely different enter situations