caculate confidence interval from customized pdf
2 views (last 30 days)
Show older comments
Hi
I'm wondering How can I caculate the confidence interval of customized pdf e.g. Gaussian mixture distribution?
pdf=@(x) w1*normpdf(x,mu1,sigma1)+w2*normpdf(x,mu2,sigma2);
cdf=@(x) integral(pdf,-Inf,x);
As icdf function only support specified distribution, I'm wondering how to caculate the shortest confidence interval?
0 Comments
Accepted Answer
David Goodmanson
on 19 Mar 2024
Edited: David Goodmanson
on 19 Mar 2024
Hello SX,
Ordinarily to find the cdfs you would have to use numerical integration. In this case for the normal distributions, the cdf function is available. Then you can interpolate using the cdf as the independent variable. Here is an example. In the plot you get a wide minimum which you might expect.
mu1 = 1;
mu2 = 2;
sig1 = 1;
sig2 = 3;
w1 = .3;
w2 = .7;
c = .9; % confidence span, there is probably a better name for this
x = -20:.00001:20;
cdf = w1*normcdf(x,mu1,sig1) +w2*normcdf(x,mu2,sig2);
cdn = linspace(min(cdf),max(cdf)-c,1e4);
xdn = interp1(cdf,x,cdn);
cup = linspace(min(cdf)+c,max(cdf),1e4);
xup = interp1(cdf,x,cup);
figure(1); grid on
plot(xup-xdn)
[x0 ind] = min(xup-xdn);
xdn(ind) % lower end of confidence interval
xup(ind) % upper end of confidence interval
cdn(ind) % lower cdf value
cup(ind) % upper cdf value
% ans = -2.4087
% ans = 6.3858
% ans = 0.0497
% ans = 0.9497
D = xup(ind)-xdn(ind) % the result
cup(ind)-cdn(ind) % check, should be c = confidence span
% D = 8.7945
% ans = 0.9000
% try a different case, get a larger confidence interval
xtest = interp1(cdf,x,[.07 .97]);
Dtest = diff(xtest)
% xtest = -1.8602 7.1554
% Dtest = 9.0156
3 Comments
More Answers (0)
See Also
Categories
Find more on Descriptive Statistics and Visualization in Help Center and File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!