Question

I need some help with calculating cumulative distribution.

lets say I have data like that:

data = abs(randn(1000,1));

I have to calculate probability cumulative distribution and bin it to reduce amount of points. I am doing it like that (lets take bin = 50):

[n, x] = hist(data, 50);
y = cumsum(n);
y = y./max(y);

The problem is, that now I have a lot of points close to y=1, but only few close to zero. I’d like to have kind of equal distribution distribution of points (additional binning on y axis?). I hope you know what I mean 🙂 How I can do that?
Thanks!

Answer 1

So, it actually means that in your data vector many points are close to 0. The usual procedure is to transform the data using log: log2 or log10, depending on the nature of the data.

Try

[n, x] = hist(log10(data), 50);
y = cumsum(n);
y = y./max(y);

You can also try sqrt instead of log or other functions.

UPDATE

Reviewing the question after your comment I think you want to use something like this:

bin = 10.^(linspace(log10(min(data)),log10(max(data)),50));
[n, x] = hist(data, bin);
y = cumsum(n);
y = y./max(y);
plot(bin,y,'.')