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Watts

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- Thread starter Watts
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Watts

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EnumaElish

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Let U_{1} and U_{2} be two independent uniforrm random variables over the unit square. Then two independent standard normal random variables can be generated as [itex]N_1 = \sqrt{-2 \log (U_1)} \sin (2\pi U_2)[/itex] and [itex]N_2 = \sqrt{-2 \log (U_1)} \cos (2\pi U_2)[/itex].

P.S. Any software with an intrinsic normal distribution function will also do the trick.

P.S. Any software with an intrinsic normal distribution function will also do the trick.

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Watts

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Explain intrinsic normal distribution function(the intrinsic part).

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lurflurf

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The obvious method would be to generate uniform ramdon numbers on [0,1] then invert the normal CDF, but that is not computationally practical. What is often done is using the law of large numbers. The average of a large number of nonpathological random variables will be normal. Uniform randoms on [0,1] work well and are often the basis for other distributions. Also as was mentioned one could use a program/library that includes a random normal generator.Watts said:

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HallsofIvy

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Watts said:Explain intrinsic normal distribution function(the intrinsic part).

"Intrinsic" here just means that the software has a built in function that will calculate the normal distribution for you.

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