Hi,
I have a data with two columns: Column 1 is the variable, and Column 2 is the probability density. I am pasting a sample of the data, but overall cumsum(COlumn2) = 100, as it should be.
Snap4.png
Question is, how do I get the 5th percentile of Column 1 (given the probabilities associated with each number). I have tried a number of things but coming at the dead-end. APologies in advance in case its too naive.

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dpb
dpb le 6 Juin 2019
If I interpret the want correctly...let z,v be your two columns--then
ecfn=ecdf(v); % empirical cumulative distribution function values
N=fix(numel(v)/2); % first half--assume symmetric distribution
P=0.05; % desired percentile (less 50th percentile)
z05=interp1(v(1:N),z(1:N),P); % find the Pth percentile

3 commentaires

Rohit Goel
Rohit Goel le 6 Juin 2019
Thank you for the reply. The excel file is attached alongwith.
The issue with the solution is that an empirical cumulative distribution doesn't always fit the actual distribution right ? It smooths it out, which distorts the result. Since I already have the probability densities on in the 'v' column - any fast way to just do a rolling cumulative sum throughout ? That will be my CDF.
Thanks again.
dpb
dpb le 6 Juin 2019
That is what ECDF is just in convenient wrapper...the interp1 is just the prepackaged lookup for the location of the actual P requested rather than nearest.
If that's all you're looking for, then sure, just find cumsum()>P excepting you'll still have to build the summation vector to find the location as ML doesn't support syntax to search a temporary result in an expression.
Rohit Goel
Rohit Goel le 7 Juin 2019
Thank you for your help. Its done.

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John D'Errico
John D'Errico le 5 Juin 2019
Modifié(e) : John D'Errico le 5 Juin 2019

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Pretty simple actually, though it is far easier as I can give you an example, than if you posted your actual data rather than a blasted picture of numbers. A picture of numbers is not worth a thousand words. Sorry, but I refuse to type in numbers from a picture.
But do this:
  1. Set the point at -9.42 to be zero.
  2. Use cumsum.
  3. Normalize the sum to 1.
  4. Interpolate (actually reverse interpolation.) at 0.05. You can do that using interp1, where x will be the cumulative probability, and y is the column 1 variable. Linear interpolation seems right.
You could also use the 'pchip' or 'makima' options in interp1 to interpolate. Do NOT use 'spline'.

1 commentaire

Rohit Goel
Rohit Goel le 6 Juin 2019
Thank you for the reply. The excel file is attached alongwith.
The issue with the solution is that its not a linear interpolation right ? This is a t-skew distribution so the middle elements need to be given a much more weight. Sorry if I am missing something.

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