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Prediction of Civil Aviation Passenger Transportation Based on ARIMA Model 被引量:5
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作者 Xinxin Tang Guangming Deng 《Open Journal of Statistics》 2016年第5期824-834,共12页
The passenger transportation, as an important index to describe the scale of aviation passenger transport, prediction and research, can let us understand the future trend of the aviation passenger transport, according... The passenger transportation, as an important index to describe the scale of aviation passenger transport, prediction and research, can let us understand the future trend of the aviation passenger transport, according to it, the airline can make corresponding marketing strategy adjustment. Combining with the knowledge of time series let us understand the characteristics of passenger transportation change, the R software is used to fit the data, so as to establish the ARIMA(1,1,8) model to describe the civil aviation passenger transport developing trend in the future and to make reasonable predictions. 展开更多
关键词 Passenger Transportation ARIMA Model Seasonal Trend FORECAST
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Parker Test for Heteroskedasticity Based on Sample Fitted Values 被引量:1
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作者 Jingming Jiang Guangming Deng 《Open Journal of Statistics》 2021年第3期400-408,共9页
<p> <span style="font-family:Verdana;">To address the drawbacks of the traditional Parker test in multivariate linear</span><span style="font-family:;" "=""> ... <p> <span style="font-family:Verdana;">To address the drawbacks of the traditional Parker test in multivariate linear</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">models:</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">the process is cumbersome and computationally intensive,</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">we propose a new heteroscedasticity test.</span><span style="font-family:;" "=""> </span><span style="font-family:Verdana;">A new heteroskedasticity test is proposed using the fitted values of the samples as new explanatory variables, reconstructing the regression model, and giving a new heteroskedasticity test based on the significance test of the coefficients, it is also compared with the existing Parker test which is improved using the principal component idea. Numerical simulations and empirical analyses show that the improved Parker test with the fitted values of the samples proposed in this paper is superior.</span> </p> 展开更多
关键词 Multiple Linear Regression Model Parker Test Fitted Values Heteroskedasticity Test
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