| nlsList {nlme} | R Documentation |
Data is partitioned according to the levels of the grouping
factor defined in model and individual nls fits are
obtained for each data partition, using the model defined in
model.
nlsList(model, data, start, control, level, subset, na.action, pool) ## S3 method for class 'nlsList' update(object, model., ..., evaluate = TRUE)
object |
an object inheriting from class |
model |
either a nonlinear model formula, with the response on
the left of a |
model. |
Changes to the model – see |
data |
a data frame in which to interpret the variables named in
|
start |
an optional named list with initial values for the
parameters to be estimated in |
control |
a list of control values passed as the |
level |
an optional integer specifying the level of grouping to be used when multiple nested levels of grouping are present. |
subset |
an optional expression indicating the subset of the rows of
|
na.action |
a function that indicates what should happen when the
data contain |
pool |
an optional logical value that is preserved as an attribute of the
returned value. This will be used as the default for |
... |
some methods for this generic require additional arguments. None are used in this method. |
evaluate |
If |
a list of nls objects with as many components as the number of
groups defined by the grouping factor. Generic functions such as
coef, fixed.effects, lme, pairs,
plot, predict, random.effects, summary,
and update have methods that can be applied to an nlsList
object.
Pinheiro, J.C., and Bates, D.M. (2000), Mixed-Effects Models in S and S-PLUS, Springer.
nls, nlme.nlsList,
nlsList.selfStart,
summary.nlsList
fm1 <- nlsList(uptake ~ SSasympOff(conc, Asym, lrc, c0), data = CO2, start = c(Asym = 30, lrc = -4.5, c0 = 52)) summary(fm1)