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统计量模型
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  statistics models
     Bayesian inference for general order statistics models in software reliability with diffuse information and model selection method are studied.
     对一般顺序统计量模型依实行了bayesian总体参数的推断,还实行了有效的模型选择方法。
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  “统计量模型”译为未确定词的双语例句
     Grey Rank Variate Model and Its Application in Short Term Climate Prediction
     灰秩序统计量模型及其在短期气候预测中的应用
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     ORDER STATISTICS MODEL OF DEPENDENT SYSTEM FAILURE PROBABILITY AND COMMON CAUSE FAILURE ANALYSIS
     相关系统失效概率的次序统计量模型及共因失效原因分析
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     Applications in some special models of sequential order statistics and in the NHPB process are also presented.
     并且给出了主要结果在特殊的序贯次序统计量模型以及非齐次纯生过程中的应用。
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  相似匹配句对
     This improved mixing dielectric model yields an excellent fit to measured data.
     模型
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     Obviously, EVA model turns out a scientific appraisals to motivate the managers.
     该模型为:
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     The Model Identification of Order Statistic
     顺序统计量模型分辨
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     U-STATISTICS IN GENERAL REGRESSION MODEL
     一般回归模型中的U统计量
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  statistics models
Bayesian analysis of order-statistics models for ranking data
      
In this paper, a class of probability models for ranking data, the order-statistics models, is investigated.
      
Not only in the shape of the PDF itself, but also for all conditional statistics models computed from the PDF.
      
A review and some new results are presented for several cluster statistics models, solutions of which can be reduced to difference equations.
      
We obtain a sufficient condition for spontaneous symmetry breaking in continuous classical statistics models.
      
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To overcome the defect that the classical grey system model exists lager error in simulating the nonsteady series,a new grey rank variate model is intro duced.Use the new model simulate and predict the May rainfall of 14 observatories of Yunnan province.The results show that the new model has higher accurcy in simulating and predicting nonsteady series,and has better steady feature.

针对灰色系统模型在处理波动较大的序列方面存在的不足 ,提出灰秩序统计量模型 ,应用此模型对云南省 14个测站的 5月雨量进行了拟合及预报 .结果表明 ,此模型不仅具有较高的拟合及预报精度 ,同时还具有良好的稳定性 .

As the basis of reliability or failure probability analysis, load-strength interference analysis can be performed at the levels of component or system, or under the background of order statistics. According to the statistical meaning of system failure and the property of order statistics, failure probability models are developed for serial system, parallel system and k-out-of-n(F) redundant system without any assumption such as “independent system". From the order statistics models of system failure probability...

As the basis of reliability or failure probability analysis, load-strength interference analysis can be performed at the levels of component or system, or under the background of order statistics. According to the statistical meaning of system failure and the property of order statistics, failure probability models are developed for serial system, parallel system and k-out-of-n(F) redundant system without any assumption such as “independent system". From the order statistics models of system failure probability as well as the form of the probability density function of order statistics itself, it can be deduced that the system failure dependence called “common cause failure" can be well reflected through the load distribution and the strength distribution.

作为可靠性或失效概率分析的基础 ,载荷—强度干涉分析可以在零件的层次上进行 ,可以在系统的层次上进行 ,也可以在次序统计量的意义上进行。文中以典型系统形式为背景 ,根据系统失效的统计学意义以及次序统计量的性质 ,应用次序统计量 ,建立具有普适性 (不需要作独立失效假设 )的串联、并联及表决系统的失效概率模型。从所建立的次序统计量模型及次序统计量的概率密度函数本身的形式可以推论 ,共因失效这种失效相关性完全可以通过载荷分布与强度分布这两种基本参量反映出来

Bayesian inference and model selection method for software reliability growth models are studied.Software reliability growth models are used in testing stages of software development to model the error content and time inter— vals between software failures.In this paper,could avoid multiple integration using of Gibbs sampling,which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution.Bayesian inference for general order statistics models in software reliability with diffuse information...

Bayesian inference and model selection method for software reliability growth models are studied.Software reliability growth models are used in testing stages of software development to model the error content and time inter— vals between software failures.In this paper,could avoid multiple integration using of Gibbs sampling,which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution.Bayesian inference for general order statistics models in software reliability with diffuse information and model selection method are studied.For model de-determination and selection,explored goodness of fit(the error sum of squares),trend tests.The methodology develoed in this paper is exemplified with a software reliability data set introduced by SYS 2(Allen P.Nikora and Michael R.Lyu 13).

研究了软件可信成长模型的bayesian推论和模型选择方法。如果用内在错误和错误之间的时间间隔来模化成长模型,在软件开发阶段,可以非常有效的利用其成长模型。本文在解决多重积分问题时利用Gibbs抽样方法来计算出算后分布。一般顺序统计量模型依赖具有扩散算前分布特性的软件。对一般顺序统计量模型依实行了bayesian总体参数的推断,还实行了有效的模型选择方法。模型的设定和判断标准可用于利用方差相乘和的适合度鉴定和趋势鉴定。为了取得相应的值例,本文在分析错误资料时利用了AllenP.NikoraandMichaelR.Lyu[13]提出的SYS2软件错误资料。

 
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