Triple seasonal autoregressive (TSAR) models have been introduced to model time series date with three layers of seasonality; however, the Bayesian identification problem these has not tackled in literature. Therefore, this paper, we objective filling gap by presenting a procedure identify best order TSAR models. Assuming that errors are normally distributed along employing priors, i.e., normal...

Missing data can be estimated by means of interpolation, time series modelling, or exploiting statistically dependent information. The limits of when one approach is preferable to the alternatives have not been explored, but are likely to be a compromise between a signal autoregressive information, availability of future observations, stationary behaviour and the strength of the dependence with...

Using a nonstationary, bivariate autoregressive process with iid innovations, this paper shows that the bootstrap vector autoregressive causality test is inconsistent in general in the sense that its weak limit is di¤erent from that of the original causality test.