Sparse HJ Biplot: A New Methodology via Elastic Net

The HJ biplot is a multivariate analysis technique that allows us to represent both individuals and variables in space of reduced dimensions. To adapt this approach massive datasets, it necessary implement new techniques are capable reducing the dimensionality data improving interpretation. Because this, we propose modern obtaining called elastic net biplot, which applies penalty improve interpretation results. It novel algorithm sense first attempt within family regularisation methods used obtain modified loadings optimise As complement proposed method, give practical support it, package has been developed R language SparseBiplots. This fills gap exists context through penalized since addition net, also includes ridge lasso biplot. complete study, comparison made with standard disjoint some results common these analysed.