shift_pred: Perturbation algorithm to get local slopes
In sachsmc/pseupersims: Simulation Study for Predicting Pseudo-observations in Survival Analysis with Superlearner
Description
Usage
Arguments
Value
Description
Given a fitted model object with a predict method, run a perturbation algorithm
that estimates the local slope of the predicted outcome for each predictor in the
model and for each subject in the dataset.
Usage
1
shift_pred(SLobject, X, predictor)
Arguments
SLobject
The fitted model object, e.g. from superlearner_estimate
X
A dataframe to be perturbed
predictor
the predictors used the the model
Value
A data frame with the local slopes for each variable (columns) and each subject (rows)
deprecated
sachsmc/pseupersims documentation built on June 12, 2019, 1:14 p.m.
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Description Usage Arguments Value
Description
Given a fitted model object with a predict method, run a perturbation algorithm that estimates the local slope of the predicted outcome for each predictor in the model and for each subject in the dataset.
Usage
1 | shift_pred(SLobject, X, predictor)
|
Arguments
SLobject |
The fitted model object, e.g. from superlearner_estimate |
X |
A dataframe to be perturbed |
predictor |
the predictors used the the model |
Value
A data frame with the local slopes for each variable (columns) and each subject (rows)
deprecated
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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