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 ...

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) ...

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 ...