Description Usage Arguments Value Examples
View source: R/ppv_functions.R
TO DO: Add description
1 2 3 4 |
Y |
A numeric vector of outcomes, assume to equal |
X |
A |
K |
The number of cross-validation folds (default is |
sens |
The sensitivity constraint imposed on the rate of negative prediction (see description). |
learner |
A wrapper that implements the desired method for building a prediction algorithm. See TODO: ADD DOCUMENTATION FOR WRITING |
nested_cv |
A boolean indicating whether nested cross validation should
be used to estimate the distribution of the prediction function. Default ( |
nested_K |
If nested cross validation is used, how many inner folds should
there be? Default ( |
parallel |
A boolean indicating whether prediction algorithms should be
trained in parallel. Default to |
max_cvtmle_iter |
Maximum number of iterations for the bias correction
step of the CV-TMLE estimator (default |
cvtmle_ictol |
The CV-TMLE will iterate |
quantile_type |
Type of quantile estimator to be used. See quantile for description. |
prediction_list |
For power users: a list of predictions made by |
... |
Other arguments, not currently used |
A list TO DO: more documentation here.
1 2 3 4 5 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.