BTLLasso: Modelling Heterogeneity in Paired Comparison Data
Version 0.1-7

Performs 'BTLLasso' (Schauberger and Tutz, 2017: Subject-Specific Modelling of Paired Comparison Data - a Lasso-Type Penalty Approach), 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.

Package details

AuthorGunther Schauberger
Date of publication2017-10-26 10:56:51 UTC
MaintainerGunther Schauberger <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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BTLLasso documentation built on Nov. 17, 2017, 6:41 a.m.