A model for port throughput forecasting using Bayesian estimation

Capacity plays a crucial role in port’s competitive position and the growth of its market share. An investment decision to provide new port capacity should be supported by growing demand for services. However, is volatile uncertain an increasingly environment. Also, forecasting models themselves are associated with epistemic uncertainty due model parameter uncertainties. This paper applies Bayesian statistical method forecast annual throughput multipurpose Port Isafjordur Iceland. Model uncertainties thus taken into account, while handled selecting influencing macroeconomic variables based on mutual information analysis. The presented has adaptive capability as becomes available. Our results range forecasts, addition point estimate, it also accounts uncertainty, increasing reliability forecasts. support informed decision-making planning management. forecasts show constant linear containerized period 2020–2025. Noncontainerized declines rapidly over same period.