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BTLLasso (version 0.1-1)

Modelling Heterogeneity in Paired Comparison Data

Description

Performs 'BTLLasso', a method to model heterogeneity in paired comparison data. Subject-specific covariates are allowed to have an influence on the attractivity/strength of the objects. An L1 penalty on the pairwise differences between the object-specific parameters allows for both clustering of objects with regard to covariates and elimination of irrelevant covariates.

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Version

Install

install.packages('BTLLasso')

Monthly Downloads

362

Version

0.1-1

License

GPL (>= 2)

Maintainer

Gunther Schauberger

Last Published

September 7th, 2015

Functions in BTLLasso (0.1-1)

BTLLasso

Function to perform BTLLasso
ci.BTLLasso

Plot confidence intervals for BTLLasso
print.cv.BTLLasso

Print function for cv.BTLLasso objects
GLESsmall

Subset of the GLES data set with 200 observations and 4 covariates.
cv.BTLLasso

Cross-validation function for BTLLasso
singlepaths

Plot parameter paths for BTLLasso
paths

Plot covariate paths for BTLLasso
boot.BTLLasso

Bootstrap function for BTLLasso
GLES

German Longitudinal Election Study (GLES)
BTLLasso.ctrl

Control function for BTLLasso
BTLLasso-package

BTLLasso