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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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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