26 lines
862 B
R
26 lines
862 B
R
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# Goal: Show the efficiency of the mean when compared with the median
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# using a large simulation where both estimators are applied on
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# a sample of U(0,1) uniformly distributed random numbers.
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one.simulation <- function(N=100) { # N defaults to 100 if not supplied
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x <- runif(N)
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return(c(mean(x), median(x)))
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}
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# Simulation --
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results <- replicate(100000, one.simulation(20)) # Gives back a 2x100000 matrix
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# Two kernel densities --
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k1 <- density(results[1,]) # results[1,] is the 1st row
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k2 <- density(results[2,])
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# A pretty picture --
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xrange <- range(k1$x, k2$x)
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plot(k1$x, k1$y, xlim=xrange, type="l", xlab="Estimated value", ylab="")
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grid()
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lines(k2$x, k2$y, col="red")
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abline(v=.5)
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legend(x="topleft", bty="n",
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lty=c(1,1),
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col=c("black", "red"),
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legend=c("Mean", "Median"))
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