dsmmR 1.0.7

DESCRIPTION

• Removed ‘Needs Compilation : yes’ according to an email from the CRAN team.

dsmmR 1.0.6

README

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

dsmmR 1.0.5

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.

dsmmR 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.

dsmmR 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.

dsmmR 1.0.2

Documentation

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

dsmmR 1.0.1

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.