# Fitting VIs

## LabVIEW 2018 Help

Edition Date: March 2018
Part Number: 371361R-01
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Owning Palette: Mathematics VIs

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.

Example

The VIs on this palette can return mathematics error codes.

Palette ObjectDescription
B-Spline FitUses B-spline fitting to smooth a data set (X, Y).
Constrained Nonlinear Curve FitUses 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 FitUses cubic spline fitting to smooth a data set (X, Y) according to the balance parameter.
Curve FittingComputes the coefficients that best represent the input data based on the chosen model type.
Exponential FitReturns the exponential fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method.
Fitting on a SphereDetermines the best spherical fit on a cloud of points in 3D.
Gaussian Peak FitReturns the Gaussian fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method.
General Linear FitFinds 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 FitReturns the polynomial fit of polynomial order for a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method.
Linear FitReturns the linear fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method.
Logarithm FitReturns the logarithmic fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method.
Nonlinear Curve FitUses 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 FitReturns the power fit of a data set (X, Y) using the Least Square, Least Absolute Residual, or Bisquare method.
Power Fit CoefficientsReturns 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 IntervalsCalculates statistical intervals of the best power fit for a data set (X, Y). You must manually select the polymorphic instance to use.

SubpaletteDescription