Chinese translation for "arima模型"

autoregressive integrated moving average

Related Translations:

arima:  阿里马阿里芒华进华上光电华宇季节和非季节性单变量模型的极大似然估计有间（大和王子）有麻有马在马

arima naozumi:  有马直纯

arima optoelectronics:  华上光电

arima mizuka:  瑞香

arima opto:  华上光电

arima harunobu:  有马晴信有晴信

arima yoshisada:  有马义贞

arima tatsuo:  有马龙夫

arima computer:  华宇电脑

arima models:  自回归综合移动平均模型

Example Sentences:

	1.	Thispaperutilize diffeffdistant observation data of suzhou huqiu tower distortion to found regress model and arimamodel , theresultisrelativelysatisfaction 本文对苏州虎丘塔变形的不等间隔观测数据，建立了回归模型和arima模型，结果比较满意。
	2.	If the datum are less than 50 , that is to say , datum of necessary modeling are insufficient , model is often relatively poor precision by arima model 如果数据少于50个，即所需建模的数据不充分，由arima模型法得到的预测模型往往精度比较差。
	3.	Hence , by observing certain characteristics , an optimal fitting model can be selected from a prior modes family , such as arima models , regression models , threshold models , and so forth 传统的预测方法一般是根据实际观测的统计资料去拟合各种先验的模型如arima模型、回归模型等，根据其实际拟合情况，找出最合适的模型。
	4.	Arima model and dynamic pca or pls methods have been employed to deal with the non - stationary issues and made a good progress . however , there are severe limitations about those dynamic models Arima模型以及动态pca或pls方法已经应用于非平稳工程系统状态监测与故障诊断领域,但是,这些方法在非平稳系统模型中存在许多局限性。
	5.	Interesting results gained in the paper : brief review of development of shenzhen stock market in the last 10 years with its component index shows the market has experienced course from the initial to related mature 本文得到了如下有意义的结果：依据对深圳股票市场的股票成分指数的变化分析，对深圳股票市场的发展进行了简要回顾，建立了arima模型并进行了预测。
	6.	Chapter2 : traditional time series models and multivariate fuzzy time series models . the chapter introduces the vector arma model , transfer arima model , seasonal arima , and arima model of traditional time series models , and two - factors models , heuristic models , and markov models of multivariate fuzzy time series models . i devise the process of the model construction , and propose the findings 本章介绍传统时间数列模型(向量arma模型、 arima转移函数模型、季节性arima模型以及arima模型)与多变量模糊时间数列三种模型?二因子模型( two - factormodels ) 、引导式模型( heuristicmodels ) 、马可夫模型( markovmodels ) ，模型建构步骤与流程，及传统时间数列模型转换为多变量模糊时间数列模型过程，并分别针对多变量模糊时间数列三种模型提出本研究不同于先前研究之处。
	7.	Meanwhile , adjusting and optimizing the structure of investment distribution on education should be given attention . the innovation of this article are rest with : 1 ) applying granger causal relations methods to test causal relationships between education investment and economy growth ; 2 ) using time series data to built econometrical model , emphasizing education investment ' s long term feature ; 3 ) projecting future developments by arima model 本文主要创新点在于: ( 1 )利用格兰杰因果关系检验确定教育投资与经济增长之间的因果关系; ( 2 )利用时间序列数据进行建模时,着重体现了教育投资的长效性这一重要的特殊性质; ( 3 )利用齐次非平稳过程的arima模型对我国未来教育投资进行了预测。
	8.	On this foundation , and in the subject - " the macro - economy monitor and early warning system of city of jinan " , the number of data are 24 at most and results received are not too ideal directly by arima model . this text has put forward a kind of new economic time - series model - grey arima model 在此基础之上，同时在课题“济南市宏观经济监测与预警系统”中，数据个数最多只有24个，直接由arima模型法预测所得到的结果不是太理想，本文提出了一类新的经济时间序列分析建模方法一灰色arima模型法。
	9.	The second is main part , and consists of innovation point of this thesis . it introduces the process of setting up model with grey separated model and arima model . the third part is analysis of real example , and it establishes model and predicts with above - mentioned methods to datum of the subject - " the macro - economy monitor and early warning system of city of jinan " , and can makes the precision of the model raise greatly 第一部分主要介绍了灰色gm门， l ）模型和ariwi模型的一般建模过程；第二部分是主体，也是本论文的创新之处，讲述了用灰色分离模型法和arima模型法建立模型的过程；第三部分是模型的实证分析部分，对课题“济南市宏观经济监测与预警系统”中的数据用上述方法建立模型并进行预测，得到比一般灰色模型gmo ， 1厅ariffe模型更高的精度。
	10.	The analysis of time - series is important for economics statistics and forecasting . up till now , most documents adopt arima model to carry on modeling and predict to time - series analysis extensively . but arima model needs more than 50 historical statistics in model discerning , and it is difficult to collect data by quarter , month or year 时间序列分析在经济统计与预测中占有重要地位，到目前为止，大多数文献广泛采用arima模型法对时间序列分析进行建模与预测，可是arima模型法在模型识别时需要50个以上历史统计数据，这对按月、按季或按年记录的经济资料往往较难收集。

Similar Words：

"arimaru" Chinese translation, "arimasa" Chinese translation, "arimasu" Chinese translation, "arimateia" Chinese translation, "arimatsu" Chinese translation, "arimbi" Chinese translation, "arimbi indonesia" Chinese translation, "arimene" Chinese translation, "arimes" Chinese translation, "arimi" Chinese translation