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)