Advanced Customizable Order-Specific Preprocessing (Centering, Scaling, Smoothing, Derivatizing, Transformations, Baselining…).Advanced Graphical Data Set Editing and Visualization Tools.Instrument Standardization (Piece-wise Direct, Windowed Piecewise Direct, OSC, Spectral Subspace Transformation (SST), Generalized Least Squares Preprocessing…).Curve fitting and Distribution fitting and analysis tools.Self-modeling Curve Resolution, Pure Variable Methods (Multivariate Curve Resolution (MCR), Purity (compare to SIMPLSMA), CODA_DW, CompareLCMS…).
Design of Experiment (DOE) tools for designing and analyzing experiments.Linear and Non-Linear Regression (Partial Least Squares (PLS), Principal Components Regression (PCR), Multiple Linear Regression (MLR), Classical Least Squares (CLS), Support Vector Machine (SVM) Regression, Artificial Neural Networks (ANNs), Boosted Regression and Classification Trees (XGBoost), N-way PLS, Locally Weighted Regression…).Classification (SIMCA, k-nearest neighbors, PLS Discriminant Analysis (PLS-DA), Support Vector Machine Classification (SVM-DA), Artificial Neural Network Classification (ANN-DA), Boosted Regression and Classification Trees (XGBoost), Clustering (HCA)…).Data Exploration and Pattern Recognition (Principal Components Analysis (PCA), Uniform Manifold Approximation and Projection (UMAP), t-distributed Stochastic Neighbor Embedding (t-SNE), Parallel Factor Analysis (PARAFAC), ANOVA Simultaneous Components Analysis (ASCA), Multiway PCA, Tucker Models…).