怀化学院学报
懷化學院學報
부화학원학보
JOURNAL OF HUAIHUA TEACHERS COLLEGE
2014年
3期
32-35
,共4页
人均消费支出%ARIMA模型预测%灰色预测%组合预测
人均消費支齣%ARIMA模型預測%灰色預測%組閤預測
인균소비지출%ARIMA모형예측%회색예측%조합예측
the per capita consumption expenditure%ARIMA model forecast%Grey prediction%combination forecast
以1992-2012年的安徽省城镇居民人均消费支出的数据，运用多元回归与时间序列结合的模型预测、ARIMA模型预测和灰色预测三种单项预测方法，以预测的误差平方和最小为准则，建立IOWA组合预测模型，并以安徽省城镇人均消费支出为例进行实证分析，发现组合预测模型在整体上都优于每一单项预测方法，对我国居民消费支出预测和研究城镇居民人均消费具有重大意义。
以1992-2012年的安徽省城鎮居民人均消費支齣的數據，運用多元迴歸與時間序列結閤的模型預測、ARIMA模型預測和灰色預測三種單項預測方法，以預測的誤差平方和最小為準則，建立IOWA組閤預測模型，併以安徽省城鎮人均消費支齣為例進行實證分析，髮現組閤預測模型在整體上都優于每一單項預測方法，對我國居民消費支齣預測和研究城鎮居民人均消費具有重大意義。
이1992-2012년적안휘성성진거민인균소비지출적수거，운용다원회귀여시간서렬결합적모형예측、ARIMA모형예측화회색예측삼충단항예측방법，이예측적오차평방화최소위준칙，건립IOWA조합예측모형，병이안휘성성진인균소비지출위례진행실증분석，발현조합예측모형재정체상도우우매일단항예측방법，대아국거민소비지출예측화연구성진거민인균소비구유중대의의。
Based on the analysis of urban residents per capita consumption expenditure data from 1992 to 2012 in Anhui province and by using the combination of multiple regression and time series model , ARIMA model prediction and gray prediction three single forecasting method and the minimum prediction error sum of squares as the criterion , IOWA combination forecast model is set up . The author of this paper makes a case study of urban per capita consumption expenditure in Anhui province . The author finds that the combination forecast model on the whole is better than that of each single prediction methods and holds that to improve the residents'consumption expenditure and the research of urban residents'per capita consumption is of great significance .
