2.4.11 funcRank
Contents
Menu Information
Analysis:Fitting:Rank Models
Brief Information
Fit and rank multiple fitting functions
Additional Information
Minimum Origin Version Required: 9.1 SR0
This feature is OriginPro only
Command Line Usage
1.funcRank funsel.category:=Exponential funsel.funclist:={20, 21, 22, 23, 24, 25} adjrsq:=1 ssr:=1 rcs:=1 stat:=1;//Fit the active data with selected functions in the Exponential category
X-Function Execution Options
Please refer to the page for additional option switches when accessing the x-function from script
Variables
| Display Name |
Variable Name |
I/O and Type |
Default Value |
Description |
|---|---|---|---|---|
| Input Data Form | form |
Input int |
Specify the input data form.
| |
| Input Data | data |
Input XYRange |
|
Input data range. If the input data form is XY Data, you can select X, Y and Y error columns using the triangle button at the right of edit box. Optionally, just select the Y column and the XF will find the X column automatically. |
| Input Data | iz |
Input XYZRange |
|
Input data range. If the input data form is XYZ Data, you can select X, Y and Z columns using the triangle button at the right of edit box. Optionally, just select the Z column and the XF will find the X,Y column automatically. |
| Functions Selection | funsel |
Input TreeNode |
|
Functions selection in a specific category. Use the tree variable funsel.category to determine the category and funsel.funclist to determine which functions to use in this category. See the command line usage example for details.
|
| Max. Number of Iterations | iter |
Input int |
|
Specify the max number of iterations performed. |
| Adj. R-Square | adjrsq |
Input int |
|
Check to output adjusted R-square in the result report sheet. |
| Residual Sum of Squares | ssr |
Input int |
|
Check to output residual sum of squares in the result report sheet. |
| Reduced Chi-Sqr | rcs |
Input int |
|
Check to output reduced Chi-square in the result report sheet. |
| Fitting Outcome String | stat |
Input int |
|
Check this item to return a detailed fitting procedure report. It may help to determine why a fit procedure failed. |
| Report Data | rdRes |
Output ReportData |
|
The result work sheet with data stored in it. You can make a recalculation simply by clicking on the lock in the upper-left corner of the report sheet and selecting the change parameters item. |
Description
You can fit and rank multiple functions in a specified category for one dataset.
Goodness of Fit
- AIC
- Recommended criteria for nonlinear curve fitting. The model with smaller AIC value is more likely to be correct
- BIC
- Recommended criteria for nonlinear curve fitting. The model with smaller BIC value is more likely to be correct
- Adj R-Square
- The model with smaller Adj R-Square value is more likely to be correct. But please note that usually Adj R-square is a recommended criteria for linear or multiple linear models instead of nonlinear curve models.
- Residual Sum of Squares
- If there are two independent variables in the regression model, the model with smaller residual sum of squares is more likely to be correct.
- Reduced Chi-Sqr
- You can refer to this FAQ page to understand the criteria well.
Examples
- Create an empty workbook and select Data: Import from File: Single ASCII to import the file Exponential Decay.dat under <Origin EXE Folder>\Samples\Curve Fitting.
- Highlight column A and B and select Analysis:Fitting:Rank Models to open the funcRank dialog.
- Select Exponential for Category, and then select the functions ExpDec1, ExpDec2, ExpDec3, ExpDecay1, ExpDecay2 and ExpDecay3 in the Function List (hold CTRL key and click for multi-selection).
- Select all four check boxes under the Fitting Results Options branch and click OK to generate the result.
- You can see the comparison and ranking of all selected functions in the RankResults1 report sheet.
Related X-Functions
Keywords:compare models