Modeling Function Overview

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Revision as of 10:40, 19 December 2018 by imported>Scott
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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.
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)