miic - v2.0.3

v2.0.3

Features

• Release to CRAN.

• tMIIC version for temporal causal discovery on stationary time series: new mode of miic() to reconstruct networks from temporal stationary datasets (Simon et al., eLife 2024).
  The temporal mode of miic() is not activated by default and can be enabled by setting the newly added parameter mode to "TS"(Temporal Stationary). A tuning of the temporal mode is possible through a set of new parameters: max_nodes, n_layers, delta_t, mov_avg and keep_max_data.

• Addition of the 'is consequence' prior knowledge. Consequence variables are excluded from the possible contributors, edges between consequences are ignored and edges between a non consequence and a consequence are pre-oriented toward the consequence.
  Information about consequence variables can be provided to miic() in the state_order, by supplying an is_consequence column.

• iMIIC version introducing contextual variables, genuine vs putative causes and multiple enhancements to deal with very large datasets (Ribeiro-Dantas et al., iScience 2024).
  Information on contextual variables can be provided to miic() in the state_order, by supplying an is_contextualcolumn and genuine vs putative causes can be tuned by the newly added parameter ort_consensus_ratio.

• Enhancement of orientations using mutual information supremum principle for finite datasets (Cabeli et al., Why21 at NeurIPS 2021).
  The use of enhanced orientations is controlled by the newly added parameter negative_info of miic() and is activated by default.

Fixes and improvements

• Faster post-processing in R for datasets with large number of variables.

• Fix for memory overflow on shared memory space.

• The discretization of continuous variables has been improved when dealing with variables having a large number of identical values.

Breaking changes

As part of this major release, consolidation of long-pending breaking changes:

• Harmonization of exported function names using camel case.

• Harmonization of parameters and return values using snake case.

• Harmonization of abbreviations.

All the documentation has been updated accordingly, in case of issue when upgrading to this version, please consult the help of the relevant function for more information about its interface.

For the core miic() function, the main breaking changes in the interface when upgrading from the 1.5.3 release are:

in the parameters:

• cplx: renaming of the complexity term "mdl" → "bic"

• ori_proba_ratio → ort_proba_ratio

in the miic object returned:

• all.edges.summary → summary

  • Nxy_ai → n_xy_ai
  • log_confidence → info_shifted
  • infOrt → ort_inferred
  • trueOrt → ort_ground_truth
  • isOrtOk → is_inference_correct
  • isCausal → is_causal
  • proba → p_y2x, p_x2y
  • consensus → ort_consensus

• orientations.prob → triples

  • NI3 → ni3
  • Error → conflict

Still compared to 1.5.3, another important change in the behavior of miic() is that, by default, miic() no longer propagates orientations and allows latent variables discovery during orientation step.

Known issues

• Conditioning on a (very) large number of contributors can lead to a memory fault.

- R
Published by franck-simon over 1 year ago

miic - v1.5.3

Fixes and improvements

• Apply proper conditions to determine if a directed edge represents a causal relation

• Fix the check error on CRAN Solaris

• Fix some edge case bugs

- R
Published by honghaoli42 over 5 years ago

miic - v1.5.2

Fixes and improvements

• Further refactoring of the C++ code for the computation of information

• Fix minor bugs in the continuous computation

• Fix incompatibility with older versions of GCC (std::align)

- R
Published by honghaoli42 over 5 years ago

miic - v1.5.1

Fixes and improvements

• Fix various bugs in the computation of information in the presence of NA values in the dataset.

• An overhaul of the C++ code base, better memory management, computation time and code readability.

- R
Published by honghaoli42 over 5 years ago

miic - v1.5.1-rc1

Fixes and improvements

• Fix various bugs in the computation of information in the presence of NA values in the dataset.

• An overhaul of the C++ code base, better memory management, computation time and code readability.

- R
Published by honghaoli42 over 5 years ago

miic - v1.5.0

Features

• Add a column consensus to the reconstructed graph's edges summary associated with the option consistent, and a new parameter consensus_threshold accordingly.

• Add a parameter ori_proba_ratio to have more control on the orientation of edges.

Fixes and improvements

• Faster post processing in R

• Rework plot functionality

• Fix a bug in the orientation part about the log score

• Refactor of the C++ code base (orientation).

- R
Published by honghaoli42 over 5 years ago

miic - v1.5.0 submission

Features

• Add a column consensus to the reconstructed graph's edges summary associated with the option consistent, and a new parameter consensus_threshold accordingly.

• Add a parameter ori_proba_ratio to have more control on the orientation of edges.

Fixes and improvements

• Faster post processing in R

• Rework plot functionality

• Fix a bug in the orientation part about the log score

• Refactor of the C++ code base (orientation).

- R
Published by vcabeli over 5 years ago

miic - v1.4.2

• Various fixes of memory leaks
• Refactoring of confidence cut code

- R
Published by honghaoli42 over 5 years ago

miic - v1.4.2

Last fixes before CRAN resubmission

- R
Published by vcabeli over 5 years ago

miic - v1.4.0

- R
Published by honghaoli42 over 5 years ago