- 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 incpm()
function to handle missing values in the input data (#2).
- Added
params
tocpm()
output to store the input arguments (#14). - Let
"sum"
be the default value forreturn_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.
- Added support for row/column matrix as input for behavior and confounds data.
- Added more data checks to ensure the input data are in the correct format.
- Added
return_edges
argument to optionally set how to return edges in the output.
- Convert back to older version of confounds treating.
- Ensure confounds regression are now only used in feature selection.
- Fixed confounds treatment. Now confounds are used in feature selection but not in model fitting.
- Ensure sparsity threshold method work as expect.
- Some other improvements in code quality.
- Keep observation names in the output.
- Check if observation names match between neural data and behavioral data.
- Added support for confounding variables.
- Initial commit to r-universe.