View source: R/generateSensitivityCurveDatasets.R
| generateSensitivityCurveDatasets | R Documentation |
This method creates a list of datasets that can be used to create sensitivity curves. The response of the dataset is modified according to the supplied arguments.
generateSensitivityCurveDatasets(
data,
observationsToChange,
shifts,
scales,
center,
formula,
...
)
data |
dataset to be modified. |
observationsToChange |
index or logical vector indicating which observations should be modified. |
shifts |
vector of shifts that should be applied one by one to each of the modified observations. |
scales |
vector scales that should be used to scale the observations around their original center. |
center |
optional scalar used to define the center from which the observations are scaled from. If missing, the mean of all the changed observations is used. |
formula |
formula to fit the model using |
... |
all additional arguments are added to the returned list. |
Either shifts or scales need to be provided. Both are also
possible.
The argument shifts contains all the values that shall be added to
each of the observations that should be changed. One value per generated
dataset.
The argument scales contains all the values that shall be used to
move observations away from their center. If scales is provided, then
observationsToChange needs to select more than one observation.
The returned list can be passed to processFit and to any of
the fitDatasets functions. Splitting and binding of datasets
using splitDatasets and bindDatasets is not
supported.
list that can be passed to processFit and to any of
the fitDatasets functions. Only generateData is
implemented, all the other functions return an error if called.
generateAnovaDatasets
oneWay <- generateAnovaDatasets(1, 1, 10, 5)
datasets <-
generateSensitivityCurveDatasets(oneWay$generateData(1),
observationsToChange = 1:5,
shifts = -10:10,
formula = oneWay$formula)
datasets$generateData(1)
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