Description Usage Arguments Value Examples
For a fixed threshold value τ, modelPredict_VS
predicts the outcome Y for subjects in the test set.
This function also outputs the cost associated with the prediction procedure. This function is used when the baseline
covariates Z are high-dimensional.
1 | modelPredict_VS(list_fpcaFit, list_cvfit, Xtest, Ztest, startT, tau)
|
list_fpcaFit |
Obtained FPCA decomposition from |
list_cvfit |
Obtained elastic net logistic regression from |
Xtest |
Longitudinal biomarker data for subjects in the test set, matrix of testn by nTotal. Missing values are denoted by NA. |
Ztest |
Other baseline covariates for subjects in the test set. |
startT |
Time of the first prediction, denoted by t_1 in the manuscript. For instance, if the time grids are {0,1/60,2/60,...,1}, then startT = 25 means that the first prediction is made at t = 24/60. |
tau |
The threshold value τ. |
final.label |
Predicted outcome Y for subjects in the test set, vector of length testn. |
avg.cost |
Average cost when we applied this prediction procedure to the test set. |
cost |
Cost for each subject, vector of length testn. For some subjects, we make a definite decision early. For others, we follow up with a long period of time. Hence the cost is different for each individual. |
1 | # see the example from function reinforced_VS.
|
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