NEWS.md

In cpmr: Connectome Predictive Modelling in R

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.

cpmr documentation built on Oct. 6, 2024, 9:06 a.m.