summary.nlsList {nlme} | R Documentation

## Summarize an nlsList Object

### Description

The `summary` function is applied to each `nls` component of `object` to produce summary information on the individual fits, which is organized into a list of summary statistics. The returned object is suitable for printing with the `print.summary.nlsList` method.

### Usage

    ## S3 method for class 'nlsList':
    summary(object, ...)

### Arguments

`object` | an object inheriting from class `nlsList`, representing a list of `nls` fitted objects.
`...` | optional arguments to the `summary.lmList` method. One such optional argument is `pool`, a logical value indicating whether a pooled estimate of the residual standard error should be used. Default is `attr(object, "pool")`.

### Value

a list with summary statistics obtained by applying `summary` to the elements of `object`, inheriting from class `summary.nlsList`. The components of `value` are:

`call` | a list containing an image of the `nlsList` call that produced `object`.
`parameters` | a three dimensional array with summary information on the `nls` coefficients. The first dimension corresponds to the names of the `object` components, the second dimension is given by `"Value"`, `"Std. Error"`, `"t value"`, and `"Pr(>|t|)"`, corresponding, respectively, to the coefficient estimates and their associated standard errors, t-values, and p-values. The third dimension is given by the coefficients names.
`correlation` | a three dimensional array with the correlations between the individual `nls` coefficient estimates. The first dimension corresponds to the names of the `object` components. The third dimension is given by the coefficients names. For each coefficient, the rows of the associated array give the correlations between that coefficient and the remaining coefficients, by `nls` component.
`cov.unscaled` | a three dimensional array with the unscaled variances/covariances for the individual `lm` coefficient estimates (giving the estimated variance/covariance for the coefficients, when multiplied by the estimated residual errors). The first dimension corresponds to the names of the `object` components. The third dimension is given by the coefficients names. For each coefficient, the rows of the associated array give the unscaled covariances between that coefficient and the remaining coefficients, by `nls` component.
`df` | an array with the number of degrees of freedom for the model and for residuals, for each `nls` component.
`df.residual` | the total number of degrees of freedom for residuals, corresponding to the sum of residuals df of all `nls` components.
`pool` | the value of the `pool` argument to the function.
`RSE` | the pooled estimate of the residual standard error.
`sigma` | a vector with the residual standard error estimates for the individual `lm` fits.

### Author(s)

Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu

### See Also

`nlsList`, `summary`

### Examples

    data(Loblolly)
    fm1 <- nlsList(SSasymp, Loblolly)
    summary(fm1)

[Package Contents]