- When the super learning arguments are set to
NULL
inunicate()
andsunicate()
, cross-validated elastic net regressions are fit to estimate nuisance parameters instead of the previously used defaultsl3
super learners. This speeds up computation time, and makes it easier to apply these methods to small datasets by default. This doesn't affect the asymptotic behaviour of theunicate()
estimator, either.
uniCATE
is going public!
- Adding GitHub Actions for CI and CD.
- Made largely stylistic updates to internal functions to pass linting and style checks.
- Set the license to Apache 2.0
failure
argument insunicate()
has been changed toevent
.- Change to
sunicate()
behaviour: The median of thedata
argument'srelative_time
variable is now set as the defaulttime_cutoff
whentime_cutoff
isNULL
. - Change to internal
sunicate()
behaviour: When transforming wide data to a long format, no more than five unique relative times are reported for each observation. These relative times correspond to the quintiles of the relative times between the earliest relative time, and the minimum of each observations relative time and the time cutoff.
- Documentation of internal and exported functions has been cleaned.
- New package introduction in README.
- Co-authors added to DESCRIPTION
- Package description updated in DESCRIPTION
- Added
sunicate()
, theunicate()
counterpart for right-censored time-to-event outcomes. - Minor touch-ups to miscellaneous docs.