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:

VALUE:

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:

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