get_risk_obj(Y, by, max_T, id, is_for_discrete_model = T)
Y
TRUE
/FALSE
for whether the model outcome is discrete. For example, a logit model is discrete whereas what is coined an exponential model in this package is a dynamic model
risk_sets |
List of lists with one for each bin. Each of the sub lists have indices that corresponds to the entries of Y that are at risk in the bin |
min_start |
Start time of the first bin |
I_len |
Length of each bin |
d |
Number of bins |
is_event_in |
Indices for which bin an observation Y is an event. -1 if the individual does not die in any of the bins |