Description Usage Arguments Value
A function for prediction based on an object of class "SurvGRP"; models fit by SurvGPR
. See github.com/ajmolstad/SurvGPR for examples.
1 | SurvGPR_Predict(results, barT, Z.full, K.full, train.inds, test.inds, times=NULL)
|
results |
An object of class "SurvGPR" obtained from fitting a model using |
barT |
A vector of length n_{\rm train} to be used for prediction. This should contain the log-survival times of the training (and/or their imputed values). If the training data is that which we used to fit the “result” object, this should be the |
Z.full |
A matrix of dimension (n_{\rm train} + n_{\rm test}) \times q with the same covariates (arranged in the same order) as Z used to obtain “results”. Note that n_{\rm train} must be the dimension of |
K.full |
Kernel matrices corresponding to the first M variance components of |
train.inds |
The indices of |
test.inds |
The indices of |
times |
A vector of times (on the original scale) at which we want to evaluate a survival function for the testing data. |
test.inds |
The indices of |
log.pred |
The predicted log-survival times for the testing subjects. |
survFunc |
An n_{\rm test} \times {\rm length}(\texttt{times}) matrix containing the estimated survival curves. The kth row is the estimated survival curve for the kth subject in the testing data evaluated at the inputed times. |
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