Cross Validated Asked by Prolix on September 13, 2020
I am using a program that draws random values in a log-uniform distribution let say between 1 and 100.
When I plot the density of the produced values with R it looks like a log-uniform distribution with high density for small values and low densities for higher values.
But if I plot the density of the logarithm of the values [i.e. y = density(log(x))] then the density that should be uniform is undulating for small values of x and stabilizing like a uniform for bigger values. (See black line in example graph below.)
My explanation is that there is some rounding going on before taking the logarithm and that this causes the oscillation for small values because they are more affected by the rounding than bigger values.
Let's use the R version, because we can all reproduce it
If I do
x <-100^runif(1000000); plot(density(log(x)))
I get
However, if I do
x <- round(100^runif(1000000)); plot(density(log(x)))
I get the sort of thing you see (setting a bandwidth of 0.1 gets you closer)
Looking at table(log(x))[1:10] you see that the discrete values are at
log(1),
log(2),
log(3)`, and so on, and they get closer together, with smaller counts, as $x$ increases:
0 0.693147180559945 1.09861228866811 1.38629436111989 1.6094379124341
87807 111514 72896 54910 43344
1.79175946922805 1.94591014905531 2.07944154167984 2.19722457733622 2.30258509299405
36324 31011 27164 24285 21628
It looks as if the C program is rounding to the nearest integer. You could smooth more, but you'll end up spreading the offending probability below zero and above where the graph is now smooth. You really need a varying smoothing bandwidth.
Correct answer by Thomas Lumley on September 13, 2020
Get help from others!
Recent Questions
Recent Answers
© 2024 TransWikia.com. All rights reserved. Sites we Love: PCI Database, UKBizDB, Menu Kuliner, Sharing RPP