cpmr 0.1.0
New features
- Added
summary() method to summarize the results of the
CPM analysis (#8).
- Added
tidy() method to tidy the results of the CPM
analysis (#10).
- Support
na_action argument in cpm()
function to handle missing values in the input data (#2).
Enhancements
- Added
params to cpm() output to store the
input arguments (#14).
- Let
"sum" be the default value for
return_edges argument.
- Let the first two dimensions of
edges in the output be
edges and networks, respectively.
- Polish the print method of the
cpm class.
cpmr 0.0.9
New features
- Added support for row/column matrix as input for behavior and
confounds data.
Maintenance
- Added more data checks to ensure the input data are in the correct
format.
cpmr 0.0.8
- Added
return_edges argument to optionally set how to
return edges in the output.
cpmr 0.0.7
- Convert back to older version of confounds treating.
cpmr 0.0.6
- Ensure confounds regression are now only used in feature
selection.
cpmr 0.0.5
- Fixed confounds treatment. Now confounds are used in feature
selection but not in model fitting.
cpmr 0.0.4
- Ensure sparsity threshold method work as expect.
- Some other improvements in code quality.
cpmr 0.0.3
- Keep observation names in the output.
- Check if observation names match between neural data and behavioral
data.
cpmr 0.0.2
- Added support for confounding variables.
cpmr 0.0.1
- Initial commit to r-universe.