Computes the Jacobian matrix for a nonlinear regression problem.
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| procedure(regression_function), | intent(in), | pointer | :: | fun |
A pointer to the regression_function to evaluate. |
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| real(kind=real64), | intent(in) | :: | xdata(:) |
The M-element array containing x-coordinate data. |
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| real(kind=real64), | intent(in) | :: | params(:) |
The N-element array containing the model parameters. |
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| real(kind=real64), | intent(out) | :: | jac(:,:) |
The M-by-N matrix where the Jacobian will be written. |
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| logical, | intent(out) | :: | stop |
A value that the user can set in fun forcing the evaluation process to stop prior to completion. |
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| real(kind=real64), | intent(in), | optional, | target | :: | f0(:) |
An optional M-element array containing the model values using the current parameters as defined in m. This input can be used to prevent the routine from performing a function evaluation at the model parameter state defined in params. |
| real(kind=real64), | intent(out), | optional, | target | :: | f1(:) |
An optional M-element workspace array used for function evaluations. |
| real(kind=real64), | intent(in), | optional | :: | step |
The differentiation step size. The default is the square root of machine precision. |
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| class(errors), | intent(inout), | optional, | target | :: | err |
A mechanism for communicating errors and warnings to the caller. Possible warning and error codes are as follows. - FS_NO_ERROR: No errors encountered. - FS_ARRAY_SIZE_ERROR: Occurs if any of the arrays are not properly sized. - FS_MEMORY_ERROR: Occurs if there is a memory allocation error. |