Fit a generalized linear model with spline functions of predictor variables.

Purpose

This App can be used to fit a generalized linear model with spline functions of predictor variables in linear combinations. An identity link function is used, and several distributions can be selected for response (normal, binomial, poisson, gamma, and inverse gaussian distributions). 

Notes: The App needs Embedded Python and pygam library. 

Installation

1. Download the Generalized_Additive_Model.opx file, then drag-and-drop onto the Origin workspace.
2. The App will start downloading dependent Python libraries. Wait a few minutes until the download is completed and restart Origin.

Operation

1. Activate a worksheet. Click the App icon to bring up the dialog.
2. In the Input tab, select a column as Dependent Variable. Select one or multiple columns for Continuous and Categorical Independent Variables.
3. In the Settings tab, select term type (linear or spline) for continuous functions. The Interaction option can be used to add interaction terms to the model in the opened dialog. Select Error Distribution for response. Modify Maximum Iteration and Tolerance to tune the fitting.
4. In the Quantities tab, select quantities to output in the report sheet.
5. In Plots tab, select plots to output in the report sheet.
6. Click OK button.

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 GeneralizedAdditiveModelSample.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://pygam.readthedocs.io/en/latest/index.html