Quantitative Regression Analysis

These methods develop regression models which attempt to predict a quantity based on measurements of responses (x-block) and corresponding quantities (y-block) on known samples.

The y-block may contain a physical quantity which is directly related to the measurements in the x-block, or it may be a value which is indirectly related to the measured x-block values. In the latter case, the resulting model is considered an "inferential" model.

Standard Linear Modeling Methods

analysis - Graphical user interface for data analysis.

cls - Classical Least Squares regression for multivariate Y.

crossval - Cross-validation for decomposition and linear regression.

lreg - Predictions based on softmax multinomial logistic regression model.

mlr - Multiple Linear Regression for multivariate Y.

pcr - Principal components regression for multivariate Y.

pls - Partial least squares regression for multivariate Y.

stepwise_regrcls - Step-wise regression for CLS models.

Multiway Models

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

modelviewer - Visualization tool for multi-way models.

Local, Non-linear, and Other Methods

ann - Artificial Neural Network regression models.

cr - Continuum Regression for multivariate y.

frpcr - Full-ratio PCR calibration and prediction.

lwr - Locally weighted regression for univariate Y.

polypls - PLS regression with polynomial inner-relation.

ridge - Ridge regression by Hoerl-Kennard-Baldwin.

svm - SVM Support Vector Machine for regression.

svmda - SVM Support Vector Machine for classification.

xgb - Gradient Boosted Tree Ensemble for regression using XGBoost.

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

Other Topics

• Application of Models to New Data
• Model Analysis and Calculation Utilities
• Plotting Utilities
• Related Tools

(Sub topic of PLS_Toolbox_Topics)