Sorting sample from exponential

In summary: I found something about order statistics, but that seems to give answers to other questions.This might be a clue as to where you're going wrong. Order statistics are a way to describe the relative frequencies of different values in a sample, and they can be used to help identify whether a distribution is exponential or not. But they can't tell you anything about the function that's describing the distribution, or whether it's a good fit for the data you've collected.
  • #1
Gerenuk
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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?
 
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  • #2
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).
 
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  • #3
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?
 
  • #4
Maybe it can be attributed to numerical precision?
 
  • #5
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.
 
  • #6
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
 
  • #7
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.
 
  • #8
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?
 

What is an exponential distribution?

An exponential distribution is a mathematical probability distribution that models the time between events in a Poisson process. It is characterized by a constant rate of occurrence of events, and the probability of an event occurring in a certain time frame is independent of the time that has passed since the last event.

How is a sample sorted from an exponential distribution?

To sort a sample from an exponential distribution, the data points are first arranged in ascending order. Then, the cumulative distribution function (CDF) is calculated for each data point. The data points are then sorted based on their corresponding CDF values, resulting in a sample sorted from an exponential distribution.

What is the purpose of sorting a sample from an exponential distribution?

Sorting a sample from an exponential distribution allows for a better understanding of the distribution of data points. It can also be used to identify outliers and assess the fit of the data to the exponential distribution model.

How do you determine the parameters of an exponential distribution from a sorted sample?

The parameters of an exponential distribution can be determined from a sorted sample by using the method of moments or maximum likelihood estimation. These methods involve using the mean and variance of the sample to estimate the parameters of the exponential distribution.

What are some common applications of sorting a sample from an exponential distribution?

Sorting a sample from an exponential distribution is commonly used in fields such as finance, engineering, and biology. It can be used to model the time between events, such as the time between stock market crashes, the time between machine failures, or the time between cell divisions in a biological system.

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