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.