Probability Density Function using ksdensity is not normalized
조회 수: 15 (최근 30일)
이전 댓글 표시
I have a vector "columnA" of N data points. I want to find the PDF. I use:
xi = min(columnA):1e-9:max(columnA);
f = ksdensity(columnA,xi);
plot(xi,f)
But when I use trapz to integrate f:
trapz(f)/length(xi)
the value is too far from 1. Even when increasing the range of xi, I still do not get reasonable value.
답변 (3개)
VladTheInstaller
2017년 1월 15일
Actually, the output from ksdensity is normalized, but you will have to use numerical integration along the appropriate space. In your case,
trapz(xi,f)
should be close to 1.
댓글 수: 0
Image Analyst
2014년 8월 21일
Why not use hist() or histc() to get the histogram? The histogram is essentially the probability density function.
댓글 수: 0
Youssef Khmou
2014년 8월 21일
The ksdensity produces a Probability density function, no need to divide by the length of the x vector :
x=randn(200,1);
y=[min(x):0.1:max(x)];
p=ksdensity(x,y);
sum(p)
% plot(y,p)
댓글 수: 0
참고 항목
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!