bttl {BTTL} | R Documentation |
Bradley-Terry Transfer Learning
Description
Contains the main function of this package that is used to estimate the parameter of interest \alpha
. The inner workings of the function are described in Hermes et al., (2024).
Usage
bttl(y, M, c_s)
Arguments
y |
A list consisting of |
M |
Total number of objects encountered across the pairwise comparisons. |
c_s |
Constant determining the strictness of the inclusion of attributes in the informative set. Smaller values lead to smaller |
Value
alpha_est |
A vector of length |
S_hat |
A vector containing the indices of attributes that are included in |
Author(s)
Sjoerd Hermes
Maintainer: Sjoerd Hermes sjoerd.hermes@wur.nl
References
1. Hermes, S., van Heerwaarden, J., and Behrouzi, P. (2024). Multi-Attribute Preferences: A Transfer Learning Approach. arXiv preprint, arXiv:2408.10558
Examples
# we first obtain the pairwise comparison data
y <- data(eba)
# now we can fit our model
result <- bttl(y, 13, 1)