summary.nls
Summary of an nls Model Object

### Description

This is an S3 method for the function summary for objects inheriting from class nls.

### Usage

    summary.nls(object, correlation = FALSE, symbolic.cor = FALSE, ...)

### Arguments

object | A fitted non-linear least-squares model inheriting from class nls.
correlation | a logical flag, to specify if the correlation matrix of the estimated parameters will be returned and printed. This argument is not used at present.
symbolic.cor | a logical flag, if TRUE, the function will print the correlations in a symbolic form rather than as numbers. This argument is not used at present.

Value
returns a list of class summary.nls whose components call, convInfo, control, and na.action are copied from its object argument and whose other components are

formula | the formula component from object.
residuals | the weighted residuals.
sigma | the square root of the estimated variance of the random error.
df | the degrees of freedom.
cov.unscaled | a matrix of unscaled covariances of the parameter estimates.
coefficients | a matrix of four columns: estimated coefficient, standard error, t-statistic, and corresponding p-value.
parameters | same as coefficients.
correlation | if correlation is TRUE, and if there is a non-zero number of residual degrees of freedom, this component is added, to indicate the correlation matrix corresponding to the cov.unscaled,
symbolic.cor | if correlation is TRUE, and if there is a non-zero number of residual degrees of freedom, this component is added with the value of the argument symbolic.cor.
message | if object's component call has an algorithm of "port", this component is set with the value copied from object's corresponding component.
... | additional arguments passed to or from other methods.

Note
This is a method for the function summary() for objects inheriting from class nls. See summary or summary.default for the general behavior of this function and for the interpretation of object.
Examples

    library(Sdatasets)
    fit1 <- nls(circumference ~ A/(1 + exp(-(age-B)/C)), data = Orange,
                start = list(A=150, B=600, C=400))
    summary(fit1)

Package stats version 6.1.5-18
Package Index