Moving multi-point average method for determining functions of time series mean and variance

A moving multiple-point average (MMPA) method was proposed to enhance the determining precision for time series mean and variance functions, and consequently to improve the accuracy for time series modeling, analyzing and forecasting. Non-periodic part of trend item which can be obtained by the MMPA approach, and the periodic part of trend item which can be calculated by sample periodogram method, comprise the whole trend function. We can further determine the series standard deviation function. Monte Carlo simulation study shows that not only the analysis precision but also the prediction accuracy can be ensured by the established methodology.