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Back to LMFitMBS class.

LMFitMBS.LMCurve(NPar as Integer, Par as Ptr, mDat as Integer, t as Ptr, y as Ptr, control as LMFitControlMBS, status as LMFitStatusMBS, tag as variant = nil)

Type Topic Plugin Version macOS Windows Linux iOS Targets
method LMFit MBS Tools Plugin 20.0 ✅ Yes ✅ Yes ✅ Yes ✅ Yes All
Runs curve algorithm.

NPar is the number of variables (INPUT, positive integer).
Par is the solution vector (INPUT/OUTPUT, array of length n). On input it must be set to an estimated solution. On output it yields the final estimate of the solution.
mDat is the number of functions to be minimized (INPUT, positive integer). It must fulfill m>=n.

Calls evaluateCurve event to query values.

control contains INPUT variables that control the fit algorithm, as declared and explained in lmstruct.h
status contains OUTPUT variables that inform about the fit result, as declared and explained in lmstruct.h

See also:

Some examples using this method:

LMFitMBS.LMCurve(NPar as Integer, Par() as double, mDat as Integer, t() as double, y() as double, control as LMFitControlMBS, status as LMFitStatusMBS, tag as variant = nil)

Type Topic Plugin Version macOS Windows Linux iOS Targets
method LMFit MBS Tools Plugin 20.0 ✅ Yes ✅ Yes ✅ Yes ✅ Yes All
Runs curve algorithm.

NPar is the number of variables (INPUT, positive integer).
Par is the solution vector (INPUT/OUTPUT, array of length n). On input it must be set to an estimated solution. On output it yields the final estimate of the solution.
mDat is the number of functions to be minimized (INPUT, positive integer). It must fulfill m>=n.

Calls evaluateCurve event to query values.

control contains INPUT variables that control the fit algorithm, as declared and explained in lmstruct.h
status contains OUTPUT variables that inform about the fit result, as declared and explained in lmstruct.h

See also:

LMFitMBS.LMMin(NPar as Integer, Par as Ptr, mDat as Integer, control as LMFitControlMBS, status as LMFitStatusMBS, tag as variant = nil)

Type Topic Plugin Version macOS Windows Linux iOS Targets
method LMFit MBS Tools Plugin 20.0 ✅ Yes ✅ Yes ✅ Yes ✅ Yes All
Runs Levenberg-Marquardt minimization.

This routine contains the core algorithm of our library.

It minimizes the sum of the squares of m nonlinear functions in n variables by a modified Levenberg-Marquardt algorithm. The function evaluation is done by the user-provided routine 'evaluate'. The Jacobian is then calculated by a forward-difference approximation.

Parameters:

NPar is the number of variables (INPUT, positive integer).
Par is the solution vector (INPUT/OUTPUT, array of length n). On input it must be set to an estimated solution. On output it yields the final estimate of the solution. This should be memoryblock with double values.
mDat is the number of functions to be minimized (INPUT, positive integer). It must fulfill m>=n.

Calls evaluateMin event to query values.

control contains INPUT variables that control the fit algorithm, as declared and explained in lmstruct.h
status contains OUTPUT variables that inform about the fit result, as declared and explained in lmstruct.h

See also:

LMFitMBS.LMMin(NPar as Integer, Par() as double, mDat as Integer, control as LMFitControlMBS, status as LMFitStatusMBS, tag as variant = nil)

Type Topic Plugin Version macOS Windows Linux iOS Targets
method LMFit MBS Tools Plugin 20.0 ✅ Yes ✅ Yes ✅ Yes ✅ Yes All
Runs Levenberg-Marquardt minimization.

This routine contains the core algorithm of our library.

It minimizes the sum of the squares of m nonlinear functions in n variables by a modified Levenberg-Marquardt algorithm. The function evaluation is done by the user-provided routine 'evaluate'. The Jacobian is then calculated by a forward-difference approximation.

Parameters:

NPar is the number of variables (INPUT, positive integer).
Par is the solution vector (INPUT/OUTPUT, array of length n). On input it must be set to an estimated solution. On output it yields the final estimate of the solution.
mDat is the number of functions to be minimized (INPUT, positive integer). It must fulfill m>=n.

Calls evaluateMin event to query values.

control contains INPUT variables that control the fit algorithm, as declared and explained in lmstruct.h
status contains OUTPUT variables that inform about the fit result, as declared and explained in lmstruct.h

See also:

The items on this page are in the following plugins: MBS Tools Plugin.


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