bayesian analysis of the rayleigh paired comparison model under loss functions using informative prior

Considering a number of paired comparison (pc) models exists in the literature. in this paper, the posterior distribution of the parameters of the rayleigh pc model is derived using informative prior: conjugate and dirichlet. the values of the hyperparameters are elicited using prior predictive distribution. the preferences for the data of cigarette brands: goldleaf (gl), marlboro (ml), dunhill (dh) and benson hedges (bh) are collected from university students. the posterior estimates of the parameters are obtained under the loss functions: quadratic loss function (qls), weighted loss function (wls)and squared error loss function (self) with their risks. the preference and predictive probabilities are calculated. the posterior probabilities, for the hypothesis of comparing two parameters are evaluated. the graphs of marginal posterior distributions are given. appropriateness of the model is tested by chi-square.