Provide a summary output (but involving some serious computations!) of
an object of class nlsr from `nlxb`

or `nlfb`

from package
`nlsr`

.

1 2 |

`object` |
An object of class 'nlsr' |

`...` |
Currently ignored. |

`summary.nlsr`

performs a summary method for an object of class 'nlsr' that
has been created by a routine such as `nlfb`

or `nlxb`

for nonlinear
least squares problems.

Issue: When there are bounded parameters, `nls`

returns a Standard Error for each of
the parameters. However, this summary does NOT have a Jacobian value (it is set to 0)
for columns where a parameter is masked or at (or very close to) a bound. See the
`R`

code for the determination of whether we are at a bound. In this case,
users may wish to look in the ‘inst/dev-codes’ directory of this package,
where there is a script ‘seboundsnlsrx.R’ that computes the `nls()`

standard errors for comparison on a simple problem.

Issue: The `printsum()`

of this object includes the singular values of the Jacobian.
These are displayed, one per coefficient row, with the coefficients. However, the
Jacobian singular values do NOT have a direct correspondence to the coefficients
on whose display row they appear. It simply happens that there are as many Jacobian
singular values as coefficients, and this is a convenient place to display them.
The same issue applies to the gradient components.

returns an invisible copy of the `nlsr`

object.

John C Nash <nashjc@uottawa.ca>

Function `nls()`

, packages `optim`

and `optimx`

.

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.

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