Strategies for improving forecast
Abstract
Time series analysis has benefited from using computer-intensive procedures to help modelling and forecasting in more complex situations. An area that has greatly supported statistical inference is computational statistics, specifically through resampling methods such as Bootstrap. Different approaches, including those for dependent data, are reviewed. An empirical study compares the use of these methods to forecast time series of varying frequencies and extremes.