Estimating the parameters of Azzalini model by Bayesian approach under symmetric and asymmetric loss functions

This paper has been proposed to estimate the parameters of Markov based logistic model by Bayesian approach for analyzing longitudinal binary data. In Bayesian estimation selection of appropriate loss function and prior density are most important ingredient. Symmetric and asymmetric loss functions have been used for estimating parameters of two state Markov model and better performance has been observed by Bayesian estimate under squared error loss function.