Tag: Simulation

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Rick Wicklin 0
Use the Cholesky transformation to correlate and uncorrelate variables

A variance-covariance matrix expresses linear relationships between variables. Given the covariances between variables, did you know that you can write down an invertible linear transformation that "uncorrelates" the variables? Conversely, you can transform a set of uncorrelated variables into variables with given covariances. The transformation that works this magic is

Rick Wicklin 0
Random number seeds: Only the first seed matters!

The other day I encountered the following SAS DATA step for generating three normally distributed variables. Study it, and see if you can discover what is unnecessary (and misleading!) about this program: data points; drop i; do i=1 to 10; x=rannor(34343); y=rannor(12345); z=rannor(54321); output; end; run; The program creates the

Rick Wicklin 0
How to lie with a simulation

In my article on Buffon's needle experiment, I showed a graph that converges fairly nicely and regularly to the value π, which is the value that the simulation is trying to estimate. This graph is, indeed, a typical graph, as you can verify by running the simulation yourself. However, notice

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