Nonlinear Least Squares Object
- DESCRIPTION:
-
Objects of class "nls" represent the information about a structural model,
as specified by a formula.
- GENERATION:
-
This class of objects is generated by the nls function to represent
the result of using nonlinear least squares to fit a nonlinear model.
- STRUCTURE:
-
This is an object inheriting from class "nls"
with the following components:
- parameters:
-
the final value of the parameters in the estimation.
- formula:
-
the formula used for the estimation.
- call:
-
an image of the call to nls, but with all the arguments explicitly
named, so that the data component of the call always gives the data
argument, and so on.
- residuals:
-
the final value of the residuals.
- fitted.values:
-
the final value of the right side of formula.
- assign:
-
a list, mapping elements of the parameters component
to the named parameters (e.g., as specified by the
start argument).
Note that the names attribute of parameters gives the individual
names; where an element of assign is of length > 1, the individual
parameter names will be extended to be unique.
The elements of this list are weakly analogous to the terms in a
linear model, and the assign components in this sense serve the
same function in both cases.
- data:
-
optionally,
a copy of the data argument with the final value of the parameters.
This is returned if the control in the fit included data=T.
The returned data will be a parametrized data frame if the data in
the fit inherited from "data.frame".
- R:
-
the upper-triangular R matrix from a QR decomposition of the gradient
matrix at the final value of the parameters.
- SEE ALSO:
-
nls
.