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.## S3 method for class 'nlsList':
summary(object, \dots)nlsList,
representing a list of nls fitted objects.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, "poolsummary
to the elements of object, inheriting from class
summary.nlsList. The components of value are:nlsList call that
produced object.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.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.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.nls component.nls
components.pool argument to the function.lm fits.nlsList, summaryfm1 <- nlsList(SSasymp, Loblolly)
summary(fm1)Run the code above in your browser using DataLab