अमूर्त

The application research of ARMA forecasting model in prediction of medals and ranking for 2016 olympic games

Shibiao Dong


The medal number and ranking of previous Olympic Game is the focus of people’s attention. By studying the time series method, this paper applies it in predicting the number of medals. It respectively predicts the medal numbers of China, the U.S. and Russia, arrives at the medal number and ranking of China in the 2016 Olympic, obtains that China will respectively win 40 goldmedals, 25 silvermedals and 27 bronzemedalswith a total of 92 medals at the 2016 Olympic Games by using the weightedmoving average method, uses autoregressive AR model, moving average AM  model and autoregressive averageARMAmodel to respectively predict the medal condition ofAmerican andRussian in the 2016Olympics, uses SAS software to test the stationary of the data, tests the autocorrelation coefficientmodel, and ultimately determines the predicted and estimated value. It is predicted that U.S. will get 44 goldmedals, 36 silvermedals and 23 bronzemedals, a total of 103medals; Russia will get 32 goldmedals, 36 silvermedals and 23 bronze medals, a total of 91 medals; thus China will be the second


में अनुक्रमित

  • कैस
  • गूगल ज्ञानी
  • जे गेट खोलो
  • चीन राष्ट्रीय ज्ञान अवसंरचना (सीएनकेआई)
  • उद्धरण कारक
  • ब्रह्मांड IF
  • रिसर्च जर्नल इंडेक्सिंग की निर्देशिका (डीआरजेआई)
  • गुप्त खोज इंजन लैब्स
  • आईसीएमजेई

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