# aldvmm 0.8.3

# aldvmm 0.8.4

- Bugfix in summary.aldvmm(): AIC was displayed instead of BIC in
summary table.
- Bugfix in predict.aldvmm(): Fitted values from aldvmm object were
supplied instead of predictions from predict.aldvmm().
- Updated vignette: Added example code for calculation of standard
errors of average treatment effects on the treated.

# aldvmm 0.8.5

- Update of validate_aldvmm(): Checking for class type of model
formula using base::inherits() instead of if(class(obj) ==
“formula”).
- Update of vignette: Include figures as .eps files to avoid loading
ggplot objects from previous versions of ggplot2

# aldvmm 0.8.6

- Default optimization method was changed to “BFGS”.
- New methods for generic functions print(), summary(),
stats::predict(), stats::coef(), stats::nobs(), stats::vcov(),
stats::model.matrix() and sandwich::estfun() are available. Objects of
class “aldvmm” can now be supplied to sandwich::sandwich(),
sandwich::vcovCL(), lmtest::coeftest(), lmtest::coefci() and other
functions.
- New workflow using the function Formula::formula() to handle models
with two right-hand sides.
- Objects of class “aldvmm” include new elements:
- n: The number of complete observations.
- df.null: Degrees of freedom of null model.
- df.residual: Degrees of freedom of fitted model.
- iter: The number of iterations during optimization.
- convergence: An indicator of successful completion of
optimization.
- call: A character value of the model call.
- terms: A list of terms objects for the models.
- data: A data frame of the estimation data.
- contrasts: A nested list of character values of contrasts.
- na.action: An object indicating the na.action used in
stats::model.frame()

# aldvmm 0.8.7

- The package “aldvmm” now uses analytical gradients instead of
numerical approximations during optimization and in methods used for
estimators from the “sandwich” package.
- New methods for generic functions stats::formula(),
stats::residuals() and stats::update(). Objects of class “aldvmm” can
now be supplied to sandwich::sandwich(), sandwich::vcovCL(),
sandwich::vcovPL(), sandwich::vcovHAC() and sandwich::vcovBS().
sandwich::vcovBS() allows re-estimating the covariance matrix using
bootstrapping with and without clustering.
- Objects of class “aldvmm” now include predicted probabilities of
component membership for all observations in the estimation data.
- New html vignette.

# aldvmm 0.8.8

- The optimizer package was changed from “optimr” to “optimx”. The
functionality remains identical.