We consider the application of the Bayesian inference approach to demand parameter estimation, implementing it with WinBUGS software based on airline seat booking data. Specifically, this research presents a statistical analysis data using Markov Chai...
We consider the application of the Bayesian inference approach to demand parameter estimation, implementing it with WinBUGS software based on airline seat booking data. Specifically, this research presents a statistical analysis data using Markov Chain Monte Carlo (MCMC) techniques based on real airlines booking data. Markov Chain Monte Carlo method is usually used to obtain estimates of posterior distribution. The non-homogeneous Poisson process (NHPP) model with gamma priors is used and several variant models are developed. Finally, computation results are presented and compared.