Changes in version 0.2.0 (2023-05-01)                  

  - New methods OPP and POP for the estimation of nu: nu_OPP_estimator()
    and nu_POP_estimator().

  - Function fit_mvt() updated using POP as default method for nu.

  - Vignette updated.

  - Functions fit_Tyler() and fit_Cauchy() now recover the missing
    scaling factor with the improved OPP-harmonic method.

  - New contributors added for OPP and POP methods: Frederic Pascal and
    Esa Ollila.

                 Changes in version 0.1.4 (2022-05-11)                  

  - No changes. Just that CRAN required to resubmit due to some issue
    with package ghyp.

                 Changes in version 0.1.3 (2022-04-16)                  

  - New method for skewed t distributions: fit_mvst()

  - New contributor added for fit_mvst(): Xiwen Wang.

  - fit_mvt() and fit_mvst(): Now the bounds for nu estimation can be
    set as a global option, e.g.: options(nu_min = 4.2).

  - Fixed description regarding covariance matrix for Cauchy
    distribution.

  - fit_mvt(): It accepts weights as argument to weight differently the
    samples (as opposed to uniform weights).

  - fit_mvt(): Many more methods to estimate nu iteratively (via
    argument nu_iterative_method).

  - fit_mvt(): New argument scale_covmat to include a correction factor
    in the covariance matrix for minimum MSE (still in development).

                 Changes in version 0.1.2 (2020-01-07)                  

  - Vignette revised: detailed descriptions of the algorithms included.

  - Comparison with additional existing benchmark sn::selm() included in
    the vignette.

  - Now the three fitting functions also return the number of iterations
    and elapsed cpu_time.

  - Significant revision of the fitting function fit_mvt(); in
    particular:
    
      - the nu_target for the estimation of nu has been removed since it
        was not effective;
      - several new options for the initial value of nu or fixed value
        of nu have been included; and
      - improved and more robust estimation of nu at each EM iteration.

  - Function fit_mvt() now allows the choice (via the argument na_rm) to
    drop the observations with NAs or impute them.

                 Changes in version 0.1.1 (2019-11-22)                  

  - Initial release is on CRAN.

  - It includes three functions for heavy tails fitting: fit_mvt(),
    fit_Tyler(), and fit_Cauchy().

  - Vignette illustrates its use and comparison with existing packages.

  - Tests are included.

  - fit_mvt() can deal with NAs and a factor model structure on the
    covariance matrix.

                        Changes in version 0.1.0                        

  - Initial bare-bone implementation (not publicly released).