Changes in version 0.9.0 (2025-11-21)                  

  - The functions aldvmm.ll() and aldvmm.sc() were vectorized to
    increase readability and computation speed.
  - The functions aldvmm.ll() and aldvmm.sc() include a numerically
    stabilized multinomial logit density to improve convergence.
  - The pdf vignette was removed.
  - The html vignette was updated to discuss the numerical properties
    and results of the stabilized likelihood and gradient functions.

                 Changes in version 0.8.8 (2023-10-28)                  

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

                 Changes in version 0.8.7 (2023-07-08)                  

  - 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.

                 Changes in version 0.8.6 (2023-06-06)                  

  - 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()

                 Changes in version 0.8.5 (2022-10-11)                  

  - 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

                 Changes in version 0.8.4 (2021-07-19)                  

  - 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.

                 Changes in version 0.8.3 (2021-06-16)                  

  - Initial release on cran.