Modeling Function Overview

High-Level Modeling Functions The following output a model structure (or similar) and are generally considered "high-level" modeling functions designed for relatively simple use by less-experienced users as well as expert users.

analysis - Graphical user interface for data analysis.

caltransfer - Create or apply calibration and instrument transfer models.

cluster - KNN and K-means cluster analysis with dendrograms.

cls - Classical Least Squares regression for multivariate Y.

corrspec - Resolves correlation spectroscopy maps.

frpcr - Full-ratio PCR calibration and prediction.

knn - K-nearest neighbor classifier.

lda - Linear Discriminant Analysis.

lwr - Locally weighted regression for univariate Y.

mcr - Multivariate curve resolution with constraints.

mlr - Multiple Linear Regression for multivariate Y.

modelselector - Create or apply a model selector model.

mpca - Multi-way (unfold) principal components analysis.

npls - Multilinear-PLS (N-PLS) for true multi-way regression.

parafac - Parallel factor analysis for n-way arrays.

parafac2 - Parallel factor analysis for unevenly sized n-way arrays.

pca - Principal components analysis.

pcr - Principal components regression for multivariate Y.

pls - Partial least squares regression for multivariate Y.

plsda - Partial least squares discriminant analysis.

purity - Self-modeling mixture analysis method based on purity of variables or spectra.

simca - Soft Independent Method of Class Analogy.

svm - SVM Support Vector Machine for regression.

svmda - SVM Support Vector Machine for classification.

tld - Trilinear decomposition.

tucker - Analysis for n-way arrays.

xgb - Gradient Boosted Tree Ensemble for regression using XGBoost.

xgbda - Gradient Boosted Tree Ensemble for classification (Discriminant Analysis) using XGBoost.

Medium-Level Modeling Functions

The following provide functionality not generally available through another higher-level function and may be of use for certain analysis methods but also require more knowledge of Matlab and the methods involved.

gram - Generalized rank annihilation method.

mlpca - Maximum likelihood principal components analysis.

coda_dw - Calculates values for the Durbin_Watson criterion of columns of data set.

comparelcms_sim_interactive - Interactive interface for COMPARELCMS.

cr - Continuum Regression for multivariate y.

evolvfa - Evolving factor analysis (forward and reverse).

ewfa - Evolving window factor analysis.

glsw - Generalized least-squares weighting/preprocessing.

gram - Generalized rank annihilation method.

lwrpred - Engine for locally weighted regression models.

mlpca - Maximum likelihood principal components analysis.

polypls - PLS regression with polynomial inner-relation.

ridge - Ridge regression by Hoerl-Kennard-Baldwin.

wtfa - Window target factor analysis.

(Sub topic of Categorical_Index)