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Requires: Full Development System. This topic might not match its corresponding palette in LabVIEW depending on your operating system, licensed product(s), and target.
Use the Fitting VIs to perform curve fitting analysis or regression.
The VIs on this palette can return mathematics error codes.
| Palette Object | Description |
|---|---|
| B-Spline Fit | Uses B-spline fitting to smooth a data set. |
| Constrained Nonlinear Curve Fit | Uses either the Levenberg-Marquardt algorithm or the trust-region dogleg algorithm to determine the set of parameters that best fit the set of input data points (X, Y) as expressed by a nonlinear function y = f(x,a), where a is the set of parameters. You must manually select the polymorphic instance to use. |
| Cubic Spline Fit | Uses cubic spline fitting to smooth a data set (X, Y) according to the balance parameter. |
| Curve Fitting | Computes the coefficients that best represent the input data based on the chosen model type. |
| Exponential Fit | Returns the exponential fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method. |
| Fitting on a Sphere | Determines the best spherical fit on a cloud of points in 3D. |
| Gaussian Peak Fit | Returns the Gaussian fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method. |
| General Linear Fit | Finds the k-dimension linear curve values and the set of k-dimension linear fit coefficients, which describe the k-dimension linear curve that best represents the input data set using the Least Square, Least Absolute Residual, or Bisquare method. |
| General Polynomial Fit | Returns the polynomial fit of polynomial order for a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method. |
| Linear Fit | Returns the linear fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method. |
| Logarithm Fit | Returns the logarithmic fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method. |
| Nonlinear Curve Fit | Uses the Levenberg-Marquardt algorithm to determine the set of parameters that best fit the set of input data points (X, Y) as expressed by a nonlinear function y = f(x,a), where a is the set of parameters. You must manually select the polymorphic instance to use. |
| Power Fit | Returns the power fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method. |
| Power Fit Coefficients | Returns the amplitude and power of the power fit for a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method. |
| Power Fit Intervals | Calculates statistical intervals of the best power fit for a data set (X, Y). You must manually select the polymorphic instance to use. |
| Subpalette | Description |
|---|---|
| Advanced Curve Fitting VIs | Use the Advanced Curve Fitting VIs to compute additional fit statistics and coefficients. |
Refer to the Fitting.lvproj in the labview\examples\Mathematics\Fitting directory for an example of using the Fitting VIs.
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