GAUSSIAN PAIRED-COMPARISON MODELS

Bayesian paired comparison models based on the Gaussian additive error models for the use of expert judgements are formulated. Some limiting properties of the models are investigated. It is observed that the posterior variance cannot be made arbitrarily small by increasing the number of experts. The posterior distributions are determined by using the Gibbs sampler, and numerical examples are discussed. The value of information lost in the paired comparison process is analysed from the Bayesian point of view.