Nonlinear Curve Fitting (Levenberg-Marquardt » VI) (G Dataflow)

Conditions that terminate the fitting process.

This node terminates the fitting process if this node passes the maximum iterations threshold or reaches the tolerance threshold.

maximum iterations

Maximum number of iterations that the node runs in the fitting process.

Default: 200

tolerance

Minimum relative change in the weighted distance between y and the current fit.

Default: 1E-08

Arbitrary values passed to the strictly typed VI reference that implements the nonlinear function.

Reference to the VI that implements the nonlinear function for the fitting model.

Dependent values.

y must be greater in size than initial parameters. y must be the same size as x.

Independent values.

x must be greater in size than initial parameters. x must be the same size as y.

Weights for the observations.

If weight is unwired, this node sets all elements of weight to 1. If the length of weight does not equal the length of y, this node forces the lengths to be equal by padding the end of weight with 1 or ignoring the extra elements at the end of weight. If an element in weight is less than 0, this node uses the absolute value of the element.

Initial guess for a solution.

The success of the nonlinear curve fit depends on how close initial parameters is to the solution. Therefore, use any available resources to obtain good initial guess coefficients to the solution before you use this node.

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error	error in contains an error
If no error occurred before the node runs, the node begins execution normally. If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.	If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Default: No error

Upper and lower numeric limits for the parameters being optimized.

minimum

Smallest allowed values of the parameters being optimized.

The input must be empty or the same size as initial parameters. This input must be the same size as maximum. This input does not allow exceptional values, such as Inf, -Inf, or NaN.

Each element in minimum must be less than or equal to the corresponding element in maximum. If an element in minimum is equal to the corresponding element in maximum, this node uses the value of the element as the constant value of that variable throughout the curve fitting.

maximum

Greatest allowed values of the parameters being optimized.

The input must be empty or the same size as initial parameters. This input must be the same size as minimum. This input does not allow exceptional values, such as Inf, -Inf, or NaN.

Each element in maximum must be greater than or equal to the corresponding element in minimum. If an element in maximum is equal to the corresponding element in minimum, this node uses the value of the element as the constant value of that variable throughout the curve fitting.

Fitting method.

Default: Least Square

Values of the nonlinear function that correspond to the independent values.

Parameters that minimize the weighted mean square error between the solution vector and the observed dependent values.

Matrix of covariances.

The element in the jth row and kth column c_jk is the covariance between a_i and a_k, where a_i and a_k are the jth and kth element in best fit parameters, respectively. c_jj is the variance of a_j.

Number of times that this node called the nonlinear function in the fitting process.

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error	error in contains an error
If no error occurred before the node runs, the node begins execution normally. If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.	If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Weighted mean square error between best nonlinear fit and y.