# targeted 0.5

`cate`

now also returns the expected potential outcomes and influence functions
- Bug-fix in the
`ml_model$update()`

method
- The default scoring method for
`cv`

now only switches to log-score+brier score when the response is a factor. Custom model-scoring function (cv argument modelscore) automatically gets ‘weights’ appended to the formal-arguments.

# targeted 0.4

`alean`

: Assumption Lean inference for generalized linear model parameters
`ate`

now supports general family argument
`cate`

now supports parallelization via the future or parallel package
`ml_model`

refactored. `ML`

new wrapper for various machine learning models.
`cv`

parallelization (future or parallel package)
`riskreg_cens`

cumulative risk, restricted mean survival predictions (censored unbiased regression estimates)

# targeted 0.3

- Conditional average treatment estimator
`cate`

, `crr`

- Generic prediction model class
`ml_model`

- design
- SuperLearner wrapper
`SL`

- Average Treatment among responders
`RATE`

# targeted 0.2.0

- Weighted Naive Bayes classifer with
`NB`

- Pooled adjacent violator algorithm
`pava`

- ODE solver
`ode_solve`

- Calibration
`calibration`

- Cross-validation
`cv`

`ace`

method updated and renamed to `ate`

# targeted 0.1.1

# targeted 0.1

- Initialization of the new package
`targeted`

with implementation of augmented inverse probability weighting methods for estimation with missing data and causal inference (`aipw`

, `ace`

), and double robust methods for risk regression with binary exposure variables (`riskreg`

).