Abstract
Airport air traffic is one of the most important and hardest one among all the airport data forecasts. In this paper, the Markov Chain Monte Carlo (MCMC) method of applied theory of statistics has been introduced into the aviation sector, and the discussion on airport air traffic forecast has been conducted taking Shanghai airport as the application background. MCMC method is designed to solve the problem parameters expectations where some baysian inference can not be directly calculated. This paper conducts the iterative computation using WinBUGS, EViews is used to estimate the initial iteration parameter of the regression model, and it is on this basis that the regression equation under the MCMC method is obtained.
Highlights
In Bayesian statistical learning, the estimation of overall parameter often needs high-dimensional probability distribution function to do the integral
The Markov Chain Monte Carlo (MCMC) method of applied theory of statistics has been introduced into the aviation sector, and the discussion on airport air traffic forecast has been conducted taking Shanghai airport as the application background
MCMC methods sample succeed from a target distribution, and each sample depends on the previous one, the notion of the Markov Chain
Summary
In Bayesian statistical learning, the estimation of overall parameter often needs high-dimensional probability distribution function to do the integral. There is no clear expression of this integral, so it is very difficult to do it In this case, the Markov Chain Monte Carlo (MCMC) method is a simple and effective calculation method. The basic idea of MCMC method is to construct a Markov Chain, making its stationary distribution the posterior distribution of the parameters to be estimated, generating the samples of posterior distribution through this Markov Chain, and doing the Monte Carlo integration of the samples of Markov Chain when they reach stationary distribution. In this paper, basing on the regression model, pretreatment is done to the initial value of the MCMC model, and empirical study is done regarding the relationship between air traffic, GDP growth rate and population growth (David, 2001). We conduct three parts, including MCMC method description, Empirical research on air traffic forecast and conclusions
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