build pca model and calculate confidence intervals in matlab

main.m
% Load example data
load hald;

% Fit PCA model
[coeff, score, latent, tsquared, explained] = pca(ingredients);

% Plot scree plot to see amount of variance explained by each principal component
figure;
pareto(explained);
xlabel('Principal Component')
ylabel('Variance Explained (%)')

% Plot biplot to visualize principal components and variable loadings
figure;
biplot(coeff(:,1:2),'Scores',score(:,1:2),'VarLabels', {'X1', 'X2', 'X3', 'X4'});
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main.m
% Calculate 95% confidence intervals for first principal component
alpha = 0.05;
[pci, ~, ~, ~, ~] = coefCI(pca(ingredients), alpha);

% Display confidence intervals
disp(['95% confidence interval for coefficients of first principal component: [' num2str(pci(:,1)') ']'])
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