formula(data)
are used together with model
to construct the nonlinear model
formula. This is used in the nls
calls and, because a
selfStarting model function can calculate initial estimates for its
parameters from the data, no starting estimates need to be provided.## S3 method for class 'selfStart':
nlsList(model, data, start, control, level, subset, na.action, pool)
selfStart
model function, which calculates
initial estimates for the model parameters from data
.model
. Because no grouping factor can be specified in
model
, data
must inherit from class
groupedData
.model
. It is passed as the
start
argument to each nls
call and is required when
the nonlinear function in model
control
argument to nls
. Defaults to an empty list.data
that should be used in the fit. This can be a logical
vector, or a numeric vector indicating which observation numbers are
to be included, or a character vector of thNA
s. The default action (na.fail
) causes
nlsList
to print an error message and terminate if there are any
incomplete observations.pool
in
calculations of standard deviations or standard errors for summaries.nls
objects with as many components as the number of
groups defined by the grouping factor. A NULL
value is assigned
to the components corresponding to clusters for which the nls
algorithm failed to converge. 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.selfStart
, groupedData
, nls
,
nlme.nlsList
, nlsList.formula
fm1 <- nlsList(SSasympOff, CO2)
summary(fm1)
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