# ddhazard_boot

0th

Percentile

##### Bootstrap for ddhazard

See the vignette 'Bootstrap illustration'. The do_stratify_with_event may be useful when either cases or non-cases are very rare to ensure that the model estimation succeeds.

##### Usage
ddhazard_boot(ddhazard_fit, strata, unique_id, R = 100,
do_stratify_with_event = F, do_sample_weights = F,
LRs = ddhazard_fit$control$LR * 2^(0:(-4)), print_errors = F)
##### Arguments
ddhazard_fit

Returned object from a ddhazard call

strata

Strata to sample within. These need to be on an individual by individual basis and not rows in the design matrix

unique_id

Unique ids where entries match entries of strata

R

Number of bootstrap estimates

do_stratify_with_event

TRUE if sampling should be by strata of whether the individual has an event. An interaction factor will be made if strata is provided

do_sample_weights

TRUE if weights should be sample instead of individuals

LRs

Learning rates in decreasing order which will be used to estimate the model.

print_errors

TRUE if errors should be printed when estimations fails

##### Value

An object like returned from the boot function

ddhazard, plot