Principal Component Analysis (PCA) is widely used in data analysis and machine learning to reduce the dimensionality of a dataset. The goal is to find a set of linearly uncorrelated (orthogonal) ...

Given the increasingly routine application of principal components analysis (PCA) using asset data in creating socio-economic status (SES) indices, we review how PCAbased indices are constructed, how ...

Stéphane Dray, Julie Josse, Principal component analysis with missing values: a comparative survey of methods, Plant Ecology, Vol. 216, No. 5, Special Issue: Statistical Analysis of Ecological ...