Want help in Discretising a cummulative distribution plot.

Hi all,
Actually I want to discretize a cummulative distribution plot so that I can obtain certain bands in the cdfplot. Please see the screenshot below, it will be much helpful to visualize what i am trying to obtain. http://virgintech.org/DiscretiseCDF.JPG
Many thanks in advance!
Shahab

 Réponse acceptée

Andrew Newell
Andrew Newell le 26 Juin 2011

0 votes

It sounds like what you are after is a set of quantiles. If you have a set of data for your cdf, you can use quantile.
If you have a function for your cdf such as normcdf, you would use the inverse function ( e.g., norminv).
All the above assumes you have the Statistics Toolbox.
EDIT: I looked again at your figure and realized that the independent variable is on the vertical axis (not what I would expect). To get a plot of that sort, you could do the following:
  1. For each power level Pow(i), find the fraction of data less than or equal to Pow(i) to get your cumulative probability p(i).
  2. Plot the bands using stair(p,Pow).
A more common approach, though, would be to select your cumulative probabilities, use quantile to determine the corresponding power levels, and plot using stair(Pow,p).

Plus de réponses (1)

Shahab Khan
Shahab Khan le 27 Juin 2011

0 votes

Dear Andrew, Many thanks for your quick reply. and my apologies for replying to you late. Actually I had no internet connection yesterday so couldn't reply. Btw I have the 17520 data points and from those data points I have drawn the CDF that I showed you in the link above. Are you saying that using quantile I can get those bands in CDF?

4 commentaires

See my edited answer.
Keep in mind that responses to answers should be comments (like the one I'm writing), not answers.
many thanks again Andrew ...your help is appreciated!! I will try implementing your suggestion would let you know the result.
Btw i mistakenly added my response in answer section but now i will keep it in mind. Thanks
Hi andrew ..I tried your suggestion and it worked out :). Many thanks for your time and attention!!

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