siso_model_fit_least_squares Interface

The routine containing the ODE's being fit. To communicate model parameters and other relevant information, an instance of the [[model_information]] type is passed to the optional argument of this routine. Use the "select type" construct to access this information.

An M-element array of arrays with each array containing the measured input and output of the system being identified.

The initial condition vector for the equations in fcn.

An N-element array containing an initial guess at the parameters.
On output, the computed model parameters.

The integrator to use when solving the system equations. If not supplied, the default integrator will be used. The default integrator is a Runge-Kutta integrator (Dormand-Prince).

The index of the ODE in fcn providing the output to fit. If no value is supplied, a value of 1 will be utilized.

An optional N-element array that can be used as upper limits on the parameter values. If no upper limit is requested for a particular parameter, utilize a very large value. The internal default is to utilize huge() as a value.

An optional N-element array that can be used as lower limits on the parameter values. If no lower limit is requested for a particalar parameter, utilize a very large magnitude, but negative, value. The internal default is to utilize -huge() as a value.

An optional N-element array that, if supplied, will be used to return statistics about the fit for each parameter.

The significance level at which to evaluate the confidence intervals. The default value is 0.05 such that a 95% confidence interval is calculated.

An optional input providing custom iteration controls.

An optional input providing custom settings for the solver.

An optional output that can be used to gain information about the iterative solution and the nature of the convergence.

An optional pointer to a routine that can be used to extract iteration information.

An optional N-by-N matrix that, if supplied, will be used to return the covariance matrix.

An optional NC-element array containing the values of the independent variable at which the constraint equations are defined.

An optional NC-element array containing the constraint function values at xc.

An optional input, that must be utilized with the xc and yc inputs, but allows for the implementation of additional constraints on the solution outside of the differential equations being fitted. An example usage would be an additional set of quasi-static tests that could help identify a stiffness term, for instance. Other uses of course can be imagined.

An optional array containing weighting factors for every equation.

User-defined information to pass along to fcn. These arguments, if supplied, will be passed through to fcn by means of the [[model_information]] type.

An error handling object.

The routine containing the ODE's being fit. To communicate model parameters and other relevant information, an instance of the [[model_information]] type is passed to the optional argument of this routine. Use the "select type" construct to access this information.

An M-element array of arrays with each array containing the measured input and output of the system being identified.

An M-by-NEQN matrix of initial condition vectors for the NEQN equations in fcn, one set for each of the M sets of data in x.

An N-element array containing an initial guess at the parameters.
On output, the computed model parameters.

The integrator to use when solving the system equations. If not supplied, the default integrator will be used. The default integrator is a Runge-Kutta integrator (Dormand-Prince).

The index of the ODE in fcn providing the output to fit. If no value is supplied, a value of 1 will be utilized.

An optional N-element array that can be used as upper limits on the parameter values. If no upper limit is requested for a particular parameter, utilize a very large value. The internal default is to utilize huge() as a value.

An optional N-element array that can be used as lower limits on the parameter values. If no lower limit is requested for a particalar parameter, utilize a very large magnitude, but negative, value. The internal default is to utilize -huge() as a value.

An optional N-element array that, if supplied, will be used to return statistics about the fit for each parameter.

The significance level at which to evaluate the confidence intervals. The default value is 0.05 such that a 95% confidence interval is calculated.

An optional input providing custom iteration controls.

An optional input providing custom settings for the solver.

An optional output that can be used to gain information about the iterative solution and the nature of the convergence.

An optional pointer to a routine that can be used to extract iteration information.

An optional N-by-N matrix that, if supplied, will be used to return the covariance matrix.

An optional NC-element array containing the values of the independent variable at which the constraint equations are defined.

An optional NC-element array containing the constraint function values at xc.

An optional input, that must be utilized with the xc and yc inputs, but allows for the implementation of additional constraints on the solution outside of the differential equations being fitted. An example usage would be an additional set of quasi-static tests that could help identify a stiffness term, for instance. Other uses of course can be imagined.

An optional array containing weighting factors for every equation.

User-defined information to pass along to fcn. These arguments, if supplied, will be passed through to fcn by means of the [[model_information]] type.

An error handling object.