summary.nls {stats} | R Documentation |

`summary`

method for class `"nls"`

.

## 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), symbolic.cor = x$symbolic.cor, signif.stars = getOption("show.signif.stars"), ...)

`object` |
an object of class `"nls"` . |

`x` |
an object of class `"summary.nls"` , usually the result of a
call to `summary.nls` . |

`correlation` |
logical; if `TRUE` , the correlation matrix of
the estimated parameters is returned and printed. |

`digits` |
the number of significant digits to use when printing. |

`symbolic.cor` |
logical. If `TRUE` , print the correlations in
a symbolic form (see `symnum` ) rather than as numbers. |

`signif.stars` |
logical. If `TRUE` , “significance stars”
are printed for each coefficient. |

`...` |
further arguments passed to or from other methods. |

The distribution theory used to find the distribution of the standard errors and of the residual standard error (for t ratios) is based on linearization and is approximate, maybe very approximate.

`print.summary.nls`

tries to be smart about formatting the
coefficients, standard errors, etc. and additionally gives
“significance stars” if `signif.stars`

is `TRUE`

.

Correlations are printed to two decimal places (or symbolically): to
see the actual correlations print `summary(object)$correlation`

directly.

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 x 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
where |

`df` |
degrees of freedom, a 2-vector (p, n-p). (Here and
elsewhere n omits observations with zero weights.) |

`cov.unscaled` |
a p x 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.

[Package *stats* version 2.5.0 Index]