Changes in version 1.0.7 (2025-07-08)                  

DESCRIPTION

  - Removed 'Needs Compilation : yes' according to an email from the
    CRAN team.

                        Changes in version 1.0.6                        

README

  - Added DOI label for the JOSS paper, after the successful
    publication.

                 Changes in version 1.0.5 (2024-07-27)                  

Tests

  - Tests are now implemented for the functions of the package. Namely:
      - fit_dsmm()
      - create_sequence()
      - get_kernel()
      - parametric_dsmm()
      - nonparametric_dsmm() (@Bisaloo, 2)

Code of Conduct

  - The Contributor Covenant Code of Conduct is now added with respect
    to the JOSS publication. The CODE_OF_CONDUCT.md file can be found in
    the .github folder.

Documentation

  - get_kernel() has small changes in the description, regarding the
    reduction of dimensions when selecting a specific argument of u, v,
    l or t.

Workflows

  - The Github workflow R-hub v2 is added in .github/workflows. This
    ensures that after every github update of the online dsmmR
    repository, the CRAN checks are being made for multiple platforms
    (linux, macos, windows). This can be run manually through the
    command rhub::rhub_check(branch = 'master').

  - Another Github workflow codecov was added in .github/workflows. This
    ensures that the dsmmR package is mostly covered by the automated
    tests in place.

Errors

  - Fixed an unexpected check that was failing in the functions
    valid_p_dist(), valid_fdist_nonparametric(),
    valid_fdist_parametric() and added a cases for the f non-drifting
    case in get_fdist_parametric(). This was causing some errors to
    appear when trying to print an estimated fitted model when f was not
    drifting (Model 2).

Reference DOIs

  - For each reference cited in paper.bib, DOIs were added in the
    correct formatting. This was a small fix done for the JOSS
    publication.

Error handling

  - Increased the clarity of the string formatting for the different
    warning messages the user may encounter during his use of the
    package.

                        Changes in version 1.0.4                        

DESCRIPTION

  - fit_dsmm() gains a new attribute multi_estimation, which enables the
    estimation of a drifting semi-Markov model using multiple sequences.
    There are two possible options: avg_model and count_sum.
    
      - avg_model averages the q_i received from multiple sequences
      - count_sum adds the counts of the states for each sequence (of
        equal size) and then computes the q_i.

  - simulate.dsmm() gains a new attribute, max_seq_length, which is
    renamed from old attribute seq_length for clarity.

                        Changes in version 1.0.3                        

DESCRIPTION

  - Updated the Depends section. Now we impose the requirement for R
    >= 3.5.0, in order to make proper use of the isTRUE() and isFALSE()
    functions in the is_logical() function defined in utils.R. These
    functions will remain for their clarity.

Documentation

  - fit_dsmm() and simulate.dsmm() functions now better explain the
    difference between a sequence of states and the embedded Markov
    chain. Notably, it was specified that sequences are input in
    fit_dsmm(), specified with the argument sequence. In
    simulate.dsmm(), such a sequence is the resulting output. The
    embedded Markov chain can be seen as part of the output from
    fit_dsmm(), named emc. Furthermore, the function base::rle() is
    mentioned for clarity.

                 Changes in version 1.0.2 (2023-09-01)                  

Documentation

  - Updated the README and DESCRIPTION files with an acknowledgement
    section.

                 Changes in version 1.0.1 (2023-02-04)                  

Minor Improvements

  - Added a NEWS.md file to track changes to the package.

  - Now the fit_dsmm() function has a default value for the states
    attribute, being the sorted unique values of the sequence character
    vector attribute.

Bug fixes

  - Fixed a case where simulate.dsmm() sometimes did not function as
    expected when nsim = 1.
      - Now it is possible to specify nsim = 0, so that the simulated
        sequence will only include the initial state and its
        corresponding sojourn time, e.g. "a", "a", "a".
        
        By giving nsim = 1 , a single simulation will be made from the
        drifting semi-Markov kernel, returning for example "a", "a",
        "a", "c".

Documentation

  - Updated the documentation for simulate.dsmm(), with accordance to
    the changes made.

  - Updated the README file.
    
      - Added high-level documentation of the package.
    
      - Added installation instructions with access to the development
        version of the package through github.

  - Updated the documentation for dsmmR-package.
    
      - Added a "Community Guidelines" section, so that users can report
        errors or mistakes and contribute directly to the software
        through the newly-established open-source github page at
        https://github.com/Mavrogiannis-Ioannis/dsmmR.
    
      - Added a "Notes" section, specifying that automated tests are in
        place in order to aid the user with any false input made and,
        furthermore, to ensure that the functions used return the
        expected output.