summary.nlsList.RdThe 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, ...)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").
a list with summary statistics obtained by applying summary
to the elements of object, inheriting from class
summary.nlsList. The components of value are:
a list containing an image of the nlsList call that
produced object.
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.
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.
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.
an array with the number of degrees of freedom for the model
and for residuals, for each nls component.
the total number of degrees of freedom for
residuals, corresponding to the sum of residuals df of all nls
components.
the value of the pool argument to the function.
the pooled estimate of the residual standard error.
a vector with the residual standard error estimates for
the individual lm fits.
fm1 <- nlsList(SSasymp, Loblolly)
summary(fm1)
#> Call:
#> Model: height ~ SSasymp(age, Asym, R0, lrc) | Seed
#> Data: Loblolly
#>
#> Coefficients:
#> Asym
#> Estimate Std. Error t value Pr(>|t|)
#> 329 94.12820 7.854473 11.984025 0.0015250903
#> 327 94.94058 8.034073 11.817241 0.0012377237
#> 325 89.88487 6.107469 14.717206 0.0006432969
#> 307 110.69919 10.969922 10.091156 0.0025753994
#> 331 111.00287 11.125081 9.977713 0.0032192119
#> 311 109.98575 10.393098 10.582575 0.0032302621
#> 315 101.05622 8.088408 12.493957 0.0006267587
#> 321 127.13400 15.734953 8.079719 0.0041760501
#> 319 101.08748 7.800912 12.958419 0.0009328591
#> 301 95.66688 6.469242 14.787959 0.0004839491
#> 323 95.55627 6.178278 15.466489 0.0004783920
#> 309 113.51390 10.199357 11.129516 0.0006540778
#> 303 105.71792 7.936191 13.320991 0.0006901480
#> 305 99.17191 6.091461 16.280482 0.0006761877
#> R0
#> Estimate Std. Error t value Pr(>|t|)
#> 329 -8.250753 1.146068 -7.199181 0.006700134
#> 327 -7.757495 1.143211 -6.785709 0.006226357
#> 325 -8.759017 1.181264 -7.414952 0.004805581
#> 307 -8.169431 1.108136 -7.372226 0.006382603
#> 331 -8.462608 1.106725 -7.646532 0.006927323
#> 311 -8.558543 1.113691 -7.684848 0.008098734
#> 315 -8.443628 1.142368 -7.391340 0.002941994
#> 321 -7.679356 1.075754 -7.138578 0.005963178
#> 319 -8.502343 1.146942 -7.413052 0.004783021
#> 301 -9.078241 1.172624 -7.741816 0.003259525
#> 323 -9.665035 1.179503 -8.194157 0.003113070
#> 309 -7.595622 1.115674 -6.808100 0.002782876
#> 303 -8.906081 1.144754 -7.779906 0.003356654
#> 305 -9.916654 1.181667 -8.392087 0.004722701
#> lrc
#> Estimate Std. Error t value Pr(>|t|)
#> 329 -3.217578 0.1295370 -24.83907 1.750358e-04
#> 327 -3.229325 0.1313231 -24.59068 1.399840e-04
#> 325 -3.086219 0.1120207 -27.55043 9.918120e-05
#> 307 -3.390345 0.1439118 -23.55849 2.091688e-04
#> 331 -3.397574 0.1447737 -23.46817 2.570655e-04
#> 311 -3.362518 0.1383662 -24.30158 2.770780e-04
#> 315 -3.232825 0.1237859 -26.11625 6.945353e-05
#> 321 -3.575331 0.1692979 -21.11858 2.452645e-04
#> 319 -3.214021 0.1204012 -26.69426 1.083870e-04
#> 301 -3.116381 0.1099075 -28.35459 6.931135e-05
#> 323 -3.092266 0.1058796 -29.20549 7.171926e-05
#> 309 -3.352815 0.1334770 -25.11905 5.763078e-05
#> 303 -3.222957 0.1165915 -27.64315 7.822383e-05
#> 305 -3.084841 0.1011074 -30.51055 1.039483e-04
#>
#> Residual standard error: 0.7003965 on 42 degrees of freedom
#>