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| Ning, Wei; Kuan-jiang, Bian; Zhi-fa, Yuan. |
| Based on the 2008 Shaanxi Statistical Yearbook and the relevant data of Shaanxi GDP in the years 1952-2007, SPSS statistical software and time series analysis are used to establish ARIMA (1.2,1) time series model, according to the four steps, recognition rules and stationary test of time series under AIC criterion. ACF graph and PACF graph are used to conduct the applicability test on model. Then, the actual value and predicted value in the years 2002-2007 are compared in order to forecast the GDP of Shaanxi Province in the next 6 years based on this model. Result shows that the relative error of actual value and predicted value is within the range of 5%, and the forecasting effect of this model is relatively good. It is forecasted that the GDP of Shaanxi... |
| Tipo: Journal Article |
Palavras-chave: GDP; ARIMA model; ACF graph; PACF graph; Time series analysis; Agribusiness. |
| Ano: 2010 |
URL: http://purl.umn.edu/93238 |
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| Cirillo, Marcelo Angelo; Safadi, Thelma. |
| The basic principle of the management of institutions directed to the public attendance consists of sound information which is able to help in decision-making. Thus, the knowledge in the managemental aspect is widened enabling for improvement in service quality and reduction in expenses. It is aimed to carry out a study, showing the viability of the application of time series so that the forecasts will contribute to decision-making in the hospital context. For the accomplishment of this work, the hospital price series of the Federal University of Santa Catarina hospital was investigated, this one being made up of remarks concerning the Hospital Price Indices (HIP), portraying the monthly variations of costs related with medicines, consumption material and... |
| Tipo: Journal Article |
Palavras-chave: ARIMA model; Intervention analysis; Hospital prices. |
| Ano: 2003 |
URL: http://purl.umn.edu/43562 |
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| Fredo, Carlos Eduardo; Margarido, Mario Antonio. |
| This paper used the X-12 method, seasonal unit root and Autoregressive Integrated Moving Average Model to identify and to model the generator process of rural employment in the state of São Paulo in the period from January 1996 to December 2006. The results show that there is strong seasonal demand for occasional rural employment from April to August for several main harvests. The seasonal unit root test detected the presence of seasonal unit root. This result confirms the presence of a seasonal pattern in the rural employment time series. The ARIMA model caught the rural employment dynamism for occasional workers. It was necessary to add three moving average parameters of small orders, beyond a seasonal moving average parameter, and an autoregressive... |
| Tipo: Journal Article |
Palavras-chave: Rural employment; Seasonality; ARIMA model; X-12 method; Labor and Human Capital. |
| Ano: 2008 |
URL: http://purl.umn.edu/53854 |
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| Tu, Xiong-ling. |
| By using the data concerning China's urban-rural residents' income gap from 1978 to 2010, this paper mainly researches the application of several kinds of models in predicting China's urban-rural residents' income gap. By conducting empirical analysis, we establish ARIMA prediction model, grey prediction model and quadratic-polynomial prediction model and conduct accuracy comparison. The results show that quadratic-polynomial prediction model has excellent fitting effect. By using quadratic- polynomial prediction model, this paper conducts prediction on trend of China's urban-rural residents' income gap from 2011 to 2013, and the prediction value of income gap of urban-rural residents in China from 2011 to 2013 is 14 173.20, 15 212.92 and 16 289.67 yuan... |
| Tipo: Journal Article |
Palavras-chave: Urban-rural residents’ income gap; ARIMA model; Grey prediction model; Quadratic- polynomial model; China; Agribusiness. |
| Ano: 2011 |
URL: http://purl.umn.edu/117350 |
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