Sorting sample from exponential

  • Context: Graduate 
  • Thread starter Thread starter Gerenuk
  • Start date Start date
  • Tags Tags
    Exponential Sorting
Click For Summary

Discussion Overview

The discussion centers around the behavior of sorted samples drawn from an exponential distribution, specifically exploring the resulting distribution shape and potential deviations from expected characteristics. Participants are examining theoretical aspects, empirical observations, and possible implications of numerical methods used in sampling.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions the distribution shape of sorted samples from an exponential distribution, noting it does not appear to be exponential.
  • Another suggests that the empirical distribution function (edf) or empirical quantile function (eqf) might be relevant, referencing Donsker's theorem and its implications for convergence.
  • A participant observes systematic deviations in the tails of the empirical distribution compared to the expected exponential distribution and inquires about the nature of these deviations.
  • Another participant proposes that numerical precision might be a factor contributing to the observed deviations.
  • One participant shares results from a simulation with 10,000 samples, noting a smooth curve with linear behavior in the center and deviations in the tails, indicating a need for further verification.
  • Concerns are raised about the quality of the random number generator used, suggesting that simpler pseudorandom generators may not produce sufficiently random samples.
  • Another participant mentions a source for generating uniform random bits using atmospheric noise, highlighting the importance of testing for statistical randomness in generated data.
  • A later reply challenges the initial premise, asserting that sorting should not change the distribution if the samples were indeed drawn from an exponential distribution, questioning the understanding of the sampling process.

Areas of Agreement / Disagreement

Participants express differing views on the implications of sorting samples from an exponential distribution, with some suggesting that deviations are present while others argue that sorting should not affect the distribution. The discussion remains unresolved with multiple competing perspectives.

Contextual Notes

There are mentions of potential limitations related to numerical precision and the quality of random number generation, which may affect the empirical results observed. The discussion also highlights the dependence on the definitions and interpretations of statistical concepts.

Who May Find This Useful

This discussion may be of interest to those studying statistics, probability theory, or anyone involved in data analysis and simulation, particularly in the context of sampling from probability distributions.

Gerenuk
Messages
1,027
Reaction score
5
What is the function that I get when I take a large sample from an exponential distribution (many values from the same distribution) and sort the sample points. I'm a bit surprised it's not really exponential.
The shape seems to fit some data I have nicely, but I don't know the function to fit :(
I found something about order statistics, but that seems to give answers to other questions.

Anyone a suggestion?
 
Physics news on Phys.org
Sounds it's like either the empirical distribution function or empirical quantile function that you're looking at.

For the edf Donsker's theorem tells us that sqrt(n)*(F_n(x)-F(x)) -> B(F(x)) where B is a Brownian bridge, so for this example you'd get either 1-exp(-bx) (for the edf) or -log(1-u)/b (for the eqf).
 
Last edited:
Thanks! Hmm, quite possible. The uniform distribution seems uniform for empirical, but the exponential seems to have some systematic deviations in the tails. Is there any statement about such systematic deviations?
 
Maybe it can be attributed to numerical precision?
 
I made a run with 10000 samples and quite a smooth curve came out. The log of it is linear in the center with tails smoothly deviating in opposite direction. But I try to check that again.
 
Maybe "random number" generator you use is not random enough? It often happens if you use simplest pseudorandom generators built into programming languages, like rand().
Try something more reliable, e.g. http://root.cern.ch/root/html/TRandom1.html
http://root.cern.ch/root/html/src/TRandom1.cxx.html#URPliB
 
For uniform random bits there is the site:

http://www.random.org

The site says that it uses atmospheric noise as input to generate the random data. In terms of compression, it looks pretty good (random data can't be compressed with standard methods), but apart from that you'll probably have to run it through some analysis to test its fit for statistical randomness.
 
Gerenuk said:
What is the function that I get when I take a large sample from an exponential distribution (many values from the same distribution) and sort the sample points. I'm a bit surprised it's not really exponential.
Sorry -- this must be a dumb question, because everyone else seems to understand what you're talking about, but could you explain more clearly what you're doing? My understanding of "sort the sample points" is "put them in numerical order". That obviously will not change the distribution. If the sample points truly were sampled from an exponential distribution, then they will also have an exponential distribution after sorting. If they don't, it can only mean that you were mistaken when you thought you were sampling from an exponential distribution.

Where am I going wrong?
 

Similar threads

  • · Replies 31 ·
2
Replies
31
Views
5K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 24 ·
Replies
24
Views
3K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 7 ·
Replies
7
Views
3K
  • · Replies 13 ·
Replies
13
Views
3K
  • · Replies 9 ·
Replies
9
Views
3K
  • · Replies 3 ·
Replies
3
Views
3K
  • · Replies 30 ·
2
Replies
30
Views
5K