residuals.nlsr

prepare and display result of <code>nlsr</code> computations

Provides tools for working with nonlinear least squares problems.
For the estimation of models reliable and robust tools than nls(), where the
the Gauss-Newton method frequently stops with 'singular gradient' messages.
This is accomplished by using, where possible, analytic derivatives to compute
the matrix of derivatives and a stabilization of the solution of the estimation
equations. Tools for approximate or externally supplied derivative matrices
are included. Bounds and masks on parameters are handled properly.

John C. Nash

nlsr

Functions for Nonlinear Least Squares Solutions - Updated 2022

Duncan Murdoch

Fernando Miguez

Arkajyoti Bhattacharjee

residuals.nlsr function

<dl><dt>object</dt>
<dd>an object of class <code>nlsr</code></dd>
<dt>...</dt>
<dd>additional data needed to evaluate the modeling functions</dd></dl>

Arguments

Author

residuals.nlsr — residuals.nlsr

<dl>

<dt>object</dt>
<dd>an object of class <code>nlsr</code></dd>


<dt>...</dt>
<dd>additional data needed to evaluate the modeling functions</dd>

</dl>

residuals.nlsr: residuals.nlsr

Description

Usage

Arguments

Author