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511 Friday Feb. 23 2001 Math/Stat 511 R. Sharpley Lecture #15: Computer Simulations of Probabilistic Models
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511 Friday Feb. 23 2001 Probabilistic Simulation To perform probabilistic simulations using a Binomial random variable X, we first compute the cumulative distribution for X. In this example, we use 4 independent Bernoulli trials (n=4) with a probability of success p=1/2 on each trial.
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511 Friday Feb. 23 2001 Probabilistic Simulation To perform probabilistic simulations using a Binomial random variable X, we first compute the cumulative distribution for X. In this example, we use 4 independent Bernoulli trials (n=4) with a probability of success p=1/2 on each trial. We can think of this as stacking the probability mass function.
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511 Friday Feb. 23 2001 Probabilistic Simulation We then observe that the differences of the heights, which must add to one, partition the y-axis from 0 to 1 proportional to the probabilities.
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511 Friday Feb. 23 2001 Probabilistic Simulation We then observe that the differences of the heights, which must add to one, partition the y-axis from 0 to 1 proportional to the probabilities.
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511 Friday Feb. 23 2001 Probabilistic Simulation We then observe that the differences of the heights, which must add to one, partition the y-axis from 0 to 1 proportional to the probabilities. If we use a uniform distribution for [0,1] along the y-axis and take the inverse, we can then ‘pick’ values for X in correct proportion to their probabilities.
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511 Friday Feb. 23 2001 Probabilistic Simulation We then observe that the differences of the heights, which must add to one, partition the y-axis from 0 to 1 proportional to the probabilities. If we use a uniform distribution for [0,1] along the y-axis and take the inverse, we can then ‘pick’ values for X in correct proportion to their probabilities.
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511 Friday Feb. 23 2001 Probabilistic Simulation We then observe that the differences of the heights, which must add to one, partition the y-axis from 0 to 1 proportional to the probabilities. If we use a uniform distribution for [0,1] along the y-axis and take the inverse, we can then ‘pick’ values for X in correct proportion to their probabilities.
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511 Friday Feb. 23 2001 Probabilistic Simulation We then observe that the differences of the heights, which must add to one, partition the y-axis from 0 to 1 proportional to the probabilities. If we use a uniform distribution for [0,1] along the y-axis and take the inverse, we can then ‘pick’ values for X in correct proportion to their probabilities.
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511 Friday Feb. 23 2001 Probabilistic Simulation compute the cumulative distribution F X for X. This may involve: * *computing the probability mass distribution function f X (x) * *sum (or integrate) f to obtain the cumulative distribution F X (x) use a standard random number generator to produce random numbers between 0 and 1. use the inverse (F X ) -1 of these numbers to obtain values for x. Similar computer simulations can obtained for a general random variable X by performing the following steps:
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