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Sep 22, 2019 at 14:53 comment added Dave Then you can use that plot to compare to your simulated PDF or integrate it to approximate the CDF.
Sep 22, 2019 at 1:05 comment added efeoeo I do have the PDF but it's not analytically tractable so I can only plot it.
Sep 22, 2019 at 0:30 comment added Dave The trouble with just assessing which procedure gives the lowest variance is that either procedure could be biased. I do not think that would be a good method. For determining which procedure is more accurate. My suggestion is to do something with the PDF or CDF. Do you have an equation for the PDF or CDF of $f$?
Sep 22, 2019 at 0:22 comment added efeoeo calculating the mean isn't the point, testing the simulation procedures is.
Sep 22, 2019 at 0:20 comment added Dave Why not just calculate the mean of $f$ the usual way?
Sep 22, 2019 at 0:16 comment added efeoeo Hi. I am not sure exactly, but let me give you an example. Say you want to use proc1 and proc2 to calculate the mean of $f$. So you sample 10.000 samples from proc1 and you take the average, and you do the same for proc2. Now, the "better/more accurate procedure" should be the one whose sample mean has a smaller standard error, right? So can those standard errors be used to compare accuracy?
Sep 22, 2019 at 0:11 comment added Dave What would you like to measure as “accuracy”? Set aside for now how to measure and assess it; that’s what we’ll help you do. But what do you want to measure to determine accuracy? Two examples are discrepancies between the simulated PDFs and the population PDFs and discrepancies between the simulated CDFs and population CDFs.
Sep 22, 2019 at 0:06 answer added Alexis timeline score: 1
Sep 21, 2019 at 23:35 review First posts
Sep 21, 2019 at 23:41
Sep 21, 2019 at 23:34 history asked efeoeo CC BY-SA 4.0