The package is not frequently built as a full package yet, so it would be better to take a clone of the code, and source the various files, which are found in the "R" folder.
The three top-level functions are rowclustering, columnclustering and biclustering, all in the "clustering.R" file, and they have standard R-style manuals to explain their usage.
If you need any more help, please email louise.mcmillan@vuw.ac.nz.
When using the OSM methods, please cite:
Fernández, D., Arnold, R., & Pledger, S. (2016). Mixture-based clustering for the ordered stereotype model. Computational Statistics & Data Analysis, 93, 46-75.
@article{fernandez2016mixture,
title={Mixture-based clustering for the ordered stereotype model},
author={Fern{\'a}ndez, Daniel and Arnold, Richard and Pledger, Shirley},
journal={Computational Statistics \& Data Analysis},
volume={93},
pages={46--75},
year={2016},
publisher={Elsevier}
}
When using the POM methods, please cite:
Matechou, E., Liu, I., Fernández, D., Farias, M., & Gjelsvik, B. (2016). Biclustering models for two-mode ordinal data. psychometrika, 81(3), 611-624.
@article{matechou2016biclustering,
title={Biclustering models for two-mode ordinal data},
author={Matechou, Eleni and Liu, Ivy and Fern{\'a}ndez, Daniel and Farias, Miguel and Gjelsvik, Bergljot},
journal={psychometrika},
volume={81},
number={3},
pages={611--624},
year={2016},
publisher={Springer}
}
When using the Binary methods, please cite:
Pledger, S., & Arnold, R. (2014). Multivariate methods using mixtures: Correspondence analysis, scaling and pattern-detection. Computational Statistics & Data Analysis, 71, 241-261.
@article{pledger2014multivariate,
title={Multivariate methods using mixtures: Correspondence analysis, scaling and pattern-detection},
author={Pledger, Shirley and Arnold, Richard},
journal={Computational Statistics \& Data Analysis},
volume={71},
pages={241--261},
year={2014},
publisher={Elsevier}
}