中文摘要：

月度经济时间序列往往会受到季节因素影响，使得经济发展中的客观变化规律被遮盖或混淆。因此，使用居民消费价格指数月度数据进行物价波动趋势分析时，首先应该采用科学的方法对月度时间序列中的季节因素进行识别、分离和调整。本文使用 X-12-ARIMA和TRAMO／SEATS两种基于ARIMA模型的季节调整方法，对我N2001-2012年的定基比价格指数进行了季节调整，并对今后短期内CPI的走势进行了预测。

英文摘要：

The monthly economic time series can be affected by seasonal factors, and the real trend of the time series may be confused. So it is important to identify, separate and adjust the seasonal factors of time series while using monthly residential consumer pricing index to do research. The paper ap seasonal factors of residential consumer pricing index. pli M es X-12-ARIMA and TRAMO/SEATS methods to analyze the oreover, the paper attempts to solve the Chinese Spring Festival affects and forecasts the future trend using TRAMO/SEATS