To address the problem that the distribution feature of time series could not always be easily described due to its diversity,the likelihood function based on the asymmetric Laplace distribution was employed irrespective of the original distribution of the data.To carry out Bayesian inference on the quantile autoregression,the Metropolis-Hastings algorithm was utilized to simulate the posterior marginal distribution of quantile autoregressive parameters,which resolved the difficulties of the high dimension ...