summary.nls {stats} R Documentation

## Summarizing Non-Linear Least-Squares Model Fits

### Description

summary method for class "nls".

### Usage

## S3 method for class 'nls'
summary(object, correlation = FALSE, symbolic.cor = FALSE, ...)

## S3 method for class 'summary.nls'
print(x, digits = max(3, getOption("digits") - 3),

### Value

The function summary.nls computes and returns a list of summary statistics of the fitted model given in object, using the component "formula" from its argument, plus

 residuals the weighted residuals, the usual residuals rescaled by the square root of the weights specified in the call to nls. coefficients a p \times 4 matrix with columns for the estimated coefficient, its standard error, t-statistic and corresponding (two-sided) p-value. sigma the square root of the estimated variance of the random error \hat\sigma^2 = \frac{1}{n-p}\sum_i{R_i^2}, where R_i is the i-th weighted residual. df degrees of freedom, a 2-vector (p, n-p). (Here and elsewhere n omits observations with zero weights.) cov.unscaled a p \times p matrix of (unscaled) covariances of the parameter estimates. correlation the correlation matrix corresponding to the above cov.unscaled, if correlation = TRUE is specified and there are a non-zero number of residual degrees of freedom. symbolic.cor (only if correlation is true.) The value of the argument symbolic.cor.

The model fitting function nls, summary.
Function coef will extract the matrix of coefficients with standard errors, t-statistics and p-values.