| Calling Sequence
| SvdResult(Norm2Err,SensitivityAnalysis,SingularValuesUsed,SingularValuesDiscarded,Norm2Indep,MinNorm2Err,SolutionVector,NData)
|
| Selectors
| | Name | Type | Description |
|
| Norm2Err
| numeric | norm of approximation |Ax-b|^2 |
| SensitivityAnalysis
| list(list) | results with sensitivity analysis |
| SingularValuesUsed
| list(numeric) | singular values used |
| SingularValuesDiscarded
| list(numeric) | singular values discarded |
| Norm2Indep
| numeric | norm of independent variables, |b|^2 |
| MinNorm2Err
| numeric | |Ax-b|^2 is all sv were used |
| SolutionVector
| list(numeric) | least squares solution, x |
| NData
| posint | number of data points (dim A is n x m) |
|
| Methods
| HTMLC, print, Rand |
| Synopsis
| An SvdResult holds the result of a linear least squares
approximation.
Such an approximation is normally generated by SvdAnalysis or SvdBestBasis.
The list with the sensitivity results has 4 entries per variable.
These are the name of the variable, the result value
(the x[i] value), an estimate of the standard deviation and
the amount by which |Ax-b|^2 will increase if this variable
would not be used.
Two compute this difference, all singular values are used.
This list is sorted in decreasing order of the last argument.
The list is only produced if the global variable ComputeSensitivity
is not set to false, otherwise it is empty. |
| See also
| SvdAnalysis, SvdBestBasis |