SimsMVA: A tool for multivariate analysis of ToF-SIMS datasets
simsMVA: A tool for multivariate analysis of ToF-SIMS datasets is a scholarly work, published in 2018 in ''Chemometrics and Intelligent Laboratory Systems''. The main subjects of the publication include non-negative matrix factorization, cluster analysis, mass spectrometry, conservation and restoration of cultural heritage, data mining, fingerprint, artificial intelligence, Analytical Chemistry, MATLAB, secondary ion mass spectrometry, mass spectrum, principal component analysis, materials science, software, pattern recognition, computer science, and multivariate statistics. The paper presents a MATLAB-based software for performing principal component analysis (PCA), non-negative matrix factorisation (NMF) and k-means clustering of large analytical chemistry datasets with a particular focus on of time-of-flight secondary ions mass spectrometry (ToF-SIMS).