BTLLasso: Modelling Heterogeneity in Paired Comparison Data

Performs 'BTLLasso', a method to include different types of variables in paired comparison models and, therefore, to allow for heterogeneity between subjects. Variables can be subject-specific, object-specific and subject-object-specific and can have an influence on the attractiveness/strength of the objects. Suitable L1 penalty terms are used to cluster certain effects and to reduce the complexity of the models.

AuthorGunther Schauberger
Date of publication2017-01-17 01:05:29
MaintainerGunther Schauberger <>
LicenseGPL (>= 2)

View on CRAN

Questions? Problems? Suggestions? or email at

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.