Cannot interpret pca results

2 次查看(过去 30 天)
Jaime  de la Mota
Jaime de la Mota 2018-4-25
Hello everyone. I have generated a code which transforms a stochastic process making it dependant on uncorrelated random variables. However, the result doesn't look like the input at all. Can someone tell me why my score coefficient doesn't look like my input argument S?
if true
V = unifrnd(1,2,1,10000);
A = betarnd(2,2,1,10000);
t=50;
for i=1:t
S(i,:)=V*i+0.5*A*i^2;
theoreticalmeanS(i)=3/2*i+1/4*i^2;
meanS(i)=mean(S(i));
end
[coeff, score, latent]=pca(S');
scoreT=score';
figure('Name', 'coeff, principal component eigenvectors')
hold on
for i=1:t
plot(coeff(:,i))
end
figure
hold on
plot(S)
figure
hold on
plot(scoreT)
end
Thanks for reading.

回答(0 个)

类别

Help CenterFile Exchange 中查找有关 Dimensionality Reduction and Feature Extraction 的更多信息

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by