Cannot interpret pca results
3 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
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.
0 Kommentare
Antworten (0)
Siehe auch
Kategorien
Mehr zu Dimensionality Reduction and Feature Extraction finden Sie in Help Center und File Exchange
Produkte
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!