Calculating Percentile from a pdf
15 ビュー (過去 30 日間)
古いコメントを表示
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.
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.
0 件のコメント
採用された回答
dpb
2019 年 6 月 6 日
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 件のコメント
dpb
2019 年 6 月 6 日
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.
その他の回答 (1 件)
John D'Errico
2019 年 6 月 5 日
編集済み: John D'Errico
2019 年 6 月 5 日
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:
- Set the point at -9.42 to be zero.
- Use cumsum.
- Normalize the sum to 1.
- 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'.
参考
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!