1) product seasonal models
乘积型季节性模型
1.
This paper deals with the autocorrrelation structure of product seasonal modelsΦ(B)Φ(B~8)x_t=θ(B)■(B~8)a_t by use of autocovariance generating functions,and finds out that for p=o,the model is parametersepar able.
本文以自协方差发生函数为工具,讨论了乘积型季节性模型。
2) multiple seasonal ARIMA model
ARIMA季节乘积模型
1.
Objective:To establish a model of multiple seasonal autoregressive integrated moving average(ARIMA) (p,d,q)(P,D,Q) s on month-morbility of Bacillary Dysentery,and to explore the applications of multiple seasonal ARIMA model.
结论:通过ARIMA(0,0,1)(0,1,1)12模型与ARIMA(0,1,1)12模型对细菌性痢疾月发病数预测效果的比较,表明ARIMA季节乘积模型是一种短期预测精度较高的预测模型。
3) multiplicative seasonal model
乘积季节模型
1.
In this paper we mainly adopt the time series multiplicative seasonal model(the combination of stochastic seasonal model and ARIMA model)and multistatistic method,and make a research on the rules of development of apartment sales.
主要采用时间序列乘积季节模型(随机季节模型与ARIMA模型的结合式)及多元统计方法,对商品房市场的发展规律进行了研究。
4) ARIMA seasonal multiple model
ARIMA季节乘积混合模型
1.
Presented in this paper are traffic prediction models based on application layer,which use ARIMA seasonal multiple model(p,d,q)(P,D,Q)s for modeling and forecasting the seasonal time series from China\'s exports of a metro area network link.
因此提出基于应用层的流量预测分析模型,对国内某城域网出口链路上的应用层流量序列采用ARIMA季节乘积混合模型(p,d,q)(P,D,Q)s建模并预测。
5) seasonal mutual tendency model
季节性交乘趋势模型
6) Seasonal Model
季节性模型
1.
The Application of the Seasonal Model to the Air Temperature Forecast in Yangling Demonstration Zone;
季节性模型在杨凌示范区气温预报中的应用
2.
As the relaxation algorithm isused for identification,the forecasting error liave some decrease,In addition,we have compared this modelwith BOxJenkins seasonal model and Obtained some conclusions.
本文对文献￣［１］中的简单的具有引导变量的预报模型加以改进，建立了广义的具有引导变量的模型，采用张驰算法对模型进行辨识，预报精度得到改善，另外，本文将该模型与经典的Ｂｏｘ－Ｊｅｎｋｉｎｓ季节性模型进行了比较，得出一些结论，仿真实例说明了结论的有效性。
补充资料：季节性
季节性
seasonal
一年内某个有特征性的时期。不少传染病的发病率，每年多在一定的季节有所增加趋势。某一季节，形成某些传染病发病率增高的趋势，是与气温的高低和昆虫媒介有关，如痢疾多发生在夏季，流行性乙型脑炎多在7、8、9三个月发病。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条