BTLLasso (0.1-10)

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Modelling Heterogeneity in Paired Comparison Data.

Performs 'BTLLasso' as described by Schauberger and Tutz (2019) and Schauberger and Tutz (2017) . BTLLasso is 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.

Maintainer: Gunther Schauberger
Author(s): Gunther Schauberger

License: GPL (>= 2)

Uses: Matrix, psychotools, Rcpp, stringr, TeachingDemos

Released about 1 year ago.

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