Perform discriminant analysis with partial least squares.

Purpose

This App is used to perform discriminant analysis based on partial least squares regression, a method that extracts the most relevant feature information from samples to facilitate classification analysis.

Installation

The app requires R software (minimum required version 4.4.0) and packages (ropls, GenomeInfoDbData).

If R is installed on your computer:

1. Download the Partial_Least_Squares_Discriminant_Analysis.opx file, then drag-and-drop onto the Origin workspace.
2. The App will start downloading dependent R packages automatically. Wait a few minutes until the download is completed.

If R is NOT installed on your computer:

1. Run Origin as administrator. Download the file Partial_Least_Squares_Discriminant_Analysis.opx and install it by choosing Tools->Package Manager->Tools->Install a Package.
2. After App installation, a pop-up dialog will ask if you agree to download and install R software before it proceeds. (If automatic downloading fails, you can install the App again or download R from here.)
3. Still in Admin mode, click the App icon in Apps Gallary window once to install dependent R packages. Wait a few minutes until it is completed.

Dialog Settings

• Input
  • Independent Variables: Select data to specify the independent variables.
  • Dependent Variables: Select data to specify the dependent variables.
  • Observation Labels: Select data to specify label for observation, the labels will be show in the Score Plots.
  • Predict Response: Determine whether to predict response from the established parital least square model. If checked, Independent Variables for Prediction control is shown.
  • Independent Variables for Prediction: Select data to specify independent variables for prediction.
• Settings
  • Scale Variables: Choose a method to scale input variables.
  • Maximum Number of Factors: Specify the maximum number of factors to be in the regression model.
• Quantities
  • Standardized Coefficients: Specify whether to output the coefficients for the scaled variables.
  • VIP: Specify whether to ouput the numerical vector of Variable Importance for Prediction.
  • Loadings: Specify whether to ouput the loadings for each X and Y variables.
  • Scores: Specify whether to ouput the scores for each X and Y variables.
  • Predicted Response for Training Data: Speciify whether to output the fitted values. 
  • Residuals: Speciify whether to output the residuals.
  • X Weights: Speciify whether to output the weights for each X variable. 
• Plots
  • Standardized Coefficients Plot: Specify whether to show Standardized Coefficients Plot.
  • Variance Importance Plot: Specify whether to show the Variance Importance Plot.
  • Component Plot: Specify whether to show the Loading Plot for eigenvectors of X and Y. Specify whether to show the Score Plot for scores of X and Y. Specify factors for the X, Y and Z axis in plots. 

Sample OPJU File
This app provides a sample OPJU file.  Right click the App icon in the Apps Gallery window, and choose Show Samples Folder from the short-cut menu. A folder will open. Drag-and-drop the project file PLS-DA Sample.opju from the folder onto Origin. The Notes window in the project shows detailed steps.
Note: If you wish to save the OPJU after changing, it is recommended that you save to a different folder location (e.g. User Files Folder).

Reference

https://search.r-project.org/CRAN/refmans/lme4/html/glmer.html