The Analysis And Forecast Of The Vegetable's Price Index

In recent years,the frequent fluctuation in agricultural product prices has got more concerns by the government and public.That not only affects the development of agriculture and economy,but also causes the fluctuations of overall price level.An precise analysis and forecast of product's price based on its data feature have its own significance to the response mechanism of agricultural markets and the national micro-control.With the development of the data-mining methods and the increase of the amount of spatio-temporal data,based on the results of the domestic and foreign researches,in this paper,we use the ARIMA(Auto-regressive Integrated Moving average)model and the STARMA(spatio-temporal Auto-Regressive and Moving Average)model to analyze and forecast the vegetable's price index.In this paper,we discussed the basic theory and the modeling process of the ARIMA model and STARMA model,considering the time correlation and spatial correlation at the same time.We used the forecast results of vegetable's price index to verify the abilities of these two models and compare their advantages and disadvantages.According to the results,we can explain the spatial variability of the vegetable's price index,and create new ideas for the agricultural researches.