文件名称:ARIMA-model-algorithm
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在目前统计预测中，存在着非平稳序列分析效果差、多步预测误差较大、缺
乏系统的软件实现等问题。本文针对该类问题进行研究，提出了NARIMA方法，
该方法以ARIMA模型为基础，有效结合了游程平稳检验方法、差分平稳处理方法
、线性最小方差预测算法等，解决了传统统计预测方法中存在的上述问题
-In the current statistical forecast, there is a differential effect of non-stationary sequence analysis, multi-step prediction error, lack of system software implementation. For this kind of problem, NARIMA method, the ARIMA model, the effective combination of a smooth run-length test, the differential steady approach, the linear minimum variance prediction algorithm to solve the traditional statistical forecasting methods exist the above problems
乏系统的软件实现等问题。本文针对该类问题进行研究，提出了NARIMA方法，
该方法以ARIMA模型为基础，有效结合了游程平稳检验方法、差分平稳处理方法
、线性最小方差预测算法等，解决了传统统计预测方法中存在的上述问题
-In the current statistical forecast, there is a differential effect of non-stationary sequence analysis, multi-step prediction error, lack of system software implementation. For this kind of problem, NARIMA method, the ARIMA model, the effective combination of a smooth run-length test, the differential steady approach, the linear minimum variance prediction algorithm to solve the traditional statistical forecasting methods exist the above problems
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ARIMA model algorithm.nh
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