Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and Forecast
Time series follow the basic principles of mathematical statistics and can provide a set of scientifically based dynamic data processing methods. Using this method, various types of data can be approximated by corresponding mathematical models, and then, the internal structure and complex characteri...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/5963516 |
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| _version_ | 1850158435936501760 |
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| author | Lu Xu Weijie Chen |
| author_facet | Lu Xu Weijie Chen |
| author_sort | Lu Xu |
| collection | DOAJ |
| description | Time series follow the basic principles of mathematical statistics and can provide a set of scientifically based dynamic data processing methods. Using this method, various types of data can be approximated by corresponding mathematical models, and then, the internal structure and complex characteristics of the data can be understood essentially, so as to achieve the purpose of predicting its development trend. This paper mainly studies the combined forecasting model based on the time series model and its application. First, the application prospects and research status of the combined forecasting model, the source of time series analysis, and the status of research development at home and abroad are given, and the purpose and significance of the research topic and the research content are summarized. Then, the paper gives the relevant theories about the ARIMA model and the basic principles of model recognition and explains the method of time series smoothing. Finally, the paper uses the ARIMA model to identify and fit the time series data and then the gray forecast model to fit and predict the time series data. Finally, by assigning reasonable weights and combining these methods, a combined forecasting model is proposed and carried out. |
| format | Article |
| id | doaj-art-645980d3b9a34e23bc8cad0a1f0f8f1c |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-645980d3b9a34e23bc8cad0a1f0f8f1c2025-08-20T02:23:52ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/59635165963516Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and ForecastLu Xu0Weijie Chen1School of Economy, Fujian Normal University, Fuzhou 350117, ChinaRuijie Networks Co., Ltd., Fuzhou 350117, ChinaTime series follow the basic principles of mathematical statistics and can provide a set of scientifically based dynamic data processing methods. Using this method, various types of data can be approximated by corresponding mathematical models, and then, the internal structure and complex characteristics of the data can be understood essentially, so as to achieve the purpose of predicting its development trend. This paper mainly studies the combined forecasting model based on the time series model and its application. First, the application prospects and research status of the combined forecasting model, the source of time series analysis, and the status of research development at home and abroad are given, and the purpose and significance of the research topic and the research content are summarized. Then, the paper gives the relevant theories about the ARIMA model and the basic principles of model recognition and explains the method of time series smoothing. Finally, the paper uses the ARIMA model to identify and fit the time series data and then the gray forecast model to fit and predict the time series data. Finally, by assigning reasonable weights and combining these methods, a combined forecasting model is proposed and carried out.http://dx.doi.org/10.1155/2021/5963516 |
| spellingShingle | Lu Xu Weijie Chen Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and Forecast Complexity |
| title | Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and Forecast |
| title_full | Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and Forecast |
| title_fullStr | Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and Forecast |
| title_full_unstemmed | Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and Forecast |
| title_short | Construction and Simulation of Economic Statistics Measurement Model Based on Time Series Analysis and Forecast |
| title_sort | construction and simulation of economic statistics measurement model based on time series analysis and forecast |
| url | http://dx.doi.org/10.1155/2021/5963516 |
| work_keys_str_mv | AT luxu constructionandsimulationofeconomicstatisticsmeasurementmodelbasedontimeseriesanalysisandforecast AT weijiechen constructionandsimulationofeconomicstatisticsmeasurementmodelbasedontimeseriesanalysisandforecast |