lsqfit (MathScript RT Module Function)
Owning Class: approximation
Requires: MathScript RT Module
Syntax
x = lsqfit(fun, a0, xdata, ydata)
x = lsqfit(fun, a0, xdata, ydata, lb, ub)
[x, normres] = lsqfit(fun, a0, xdata, ydata)
[x, normres] = lsqfit(fun, a0, xdata, ydata, lb, ub)
[x, normres, resid] = lsqfit(fun, a0, xdata, ydata)
[x, normres, resid] = lsqfit(fun, a0, xdata, ydata, lb, ub)
Legacy Name: lsqcurvefit
Description
Uses the least-squares method to compute the solution to a nonlinear curve-fitting problem.
Inputs
| Name | Description |
|---|---|
| fun | Specifies the nonlinear function to fit. |
| a0 | Specifies an initial guess for the parameter vector. |
| xdata | Specifies the input data vector of the nonlinear function fun. |
| ydata | Specifies the output data vector of the nonlinear function fun. |
| lb | Specifies the lower bounds of the parameter vector. length(lb) must equal length(a0). |
| ub | Specifies the upper bounds of the parameter vector. length(ub) must equal length(a0). |
Outputs
| Name | Description |
|---|---|
| x | Returns the coefficients that minimize the mean squared error between the solution vector and the observed y-values. |
| normres | Returns the value of the squared 2-norm of the residual. |
| resid | Returns the residue of the fitted curve. |
Details
This function uses the Levenberg-Marquardt algorithm to determine the set of parameters that best fit the set of input data points (xdata, ydata) as expressed by the nonlinear function ydata = f(a, xdata), where a is the set of parameters.
The function to fit is defined by the input parameter fun, which is a script file and takes the form of the following equation:
[F, df] = myfun(a, xdata)
where F is the array of values evaluated at xdata: myfun(a, xdata), and df is a two-dimensional array of the partial derivatives at xdata with respect to the coefficients, or the Jacobian value J. The calculation of the partial derivatives is optional. If you do not calculate the derivatives in the script, df must equal zeros(0, 0), and LabVIEW calculates the derivatives numerically.
This function is not supported in the LabVIEW Run-Time Engine. Do not use this function in a stand-alone application or shared library.
Examples
% The myfun function is defined by:
%function [F, df] = myfun(a, xdata)
%F = a(1)*xdata.^2 + a(2)*cos(xdata);
%df = zeros(0, 0);
a = [2, 1.5];
x = 0:1:19;
noise = randnormal(size(x)) / 5;
y = a(1)*x.^2 + a(2)*cos(x) + noise;
[x, normres, resid] = lsqfit('myfun', [10, 10], x, y);