How to add two probability density functions efficiently
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Hello, I have a simple problem but I need to improve the execution efficiency when I have thousands of data in a probability density function, a small example:
close all
clear
%example
x =[ 1 3 5 9 15];
y =[ 4 7 8 12 6];
xn=[ 3 9 16];
yn=[ 10 3 4];
[xnew,ynew]=add2pdf(x,y,xn,yn);
xnew
ynew
% function
function [xnew,ynew]=add2pdf(x,y,xn,yn)
% sum two probability density function
[nf,nc]=size(xn);
xold=x;
yold=y;
xx=[x xn];
[xv,xp]=sort(xx,'ascend');
dxv=diff(xv);
xnew=[xv(1) xv(find(dxv>0)+1)];
ynew=zeros(1,length(xnew));
for i=1:size(y,2),
pynew=find(xnew==xold(i)); % <====this instruction it's very slow (find), but I need the pointers
ynew(pynew)=y(i);
end
for i=1:length(xn),
px=find(xnew==xn(i));
ynew(px)=ynew(px)+yn(i);
end
return
采纳的回答
David Goodmanson
2017-12-20
编辑：David Goodmanson
2017-12-20
Hi Juan,
Here is one way. It takes advantage of the fact that when you make a sparse matrix with repeated indices, the corresponding values get added. Here M is a one-row matrix.
M = full(sparse([x xn],1,[y yn]))';
xnew = find(M);
ynew = M(xnew);
3 个评论
Juan Pablo Segovia
2017-12-20
Juan Pablo Segovia
2017-12-20
David Goodmanson
2017-12-20
Juan, you're welcome, thank you for your comment. The sparse function has useful properties and did most of the work here.
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