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gamma分布参数
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  “gamma分布参数”译为未确定词的双语例句
     Bayesian Inference in Parameters of Gamma Distribution with Multiple Change Points
     Gamma分布参数多个转变点的Bayes推断
短句来源
     The gamma parameter a of the lst,nd and 3rd codon positions were 0.00572,0.01237 and 1.05239 respectively, they showed that there was adifferent substitution rate at different codon position.
     密码子第一、二和三位点的gamma分布参数α值分别为0.00572、0.01237和1.05239,表明密码子第一位点的替换速率变异最大,第二位点次之,第三位点的替换速率变异相对较小;
短句来源
     In this paper, a sufficient and essential condition of admissible estimators is given with estimator (a1 X1,……,ap Xp ) of parameter a in the Gamma distribution and weighing
     本文给出了Gamma分布参数α的估计量(α_1X_1,…,αX)′在加权平方和损失函数下为可容许估计的充分必要条件,获得了在一般损失函数L_v下它为可容许估计的充分条件(在线性估计类中)。
短句来源
     Based on this framework four parameters for precipitation simulation for each month at 672 stations all over China are determined using daily precipitation data from 1961 to 2000. Compared with previous works, our estimation for the parameters is made for more stations and longer observations, which makes the weather generator more applicable and reliable. The spatial distribution of the four parameters is analyzed in a regional climate context.
     根据中国672个气象站点1961~2000年的逐日降水资料,计算了降水转移概率P (WD)、P (WW) 及GAMMA分布参数ALPHA和BETA,并分析了4个参数在中国各地的空间分布特征与不同地区各参数的季节分布特征。
短句来源
     Methods EM algorithm was employed to construct an iterative formula for solving the maximum likelihood estimation (MLE) of parameters of Gamma distribution with interval data,whereby we can estimate the distribution parameters of SARS incubation period with interval data.
     方法采用EM算法构造出求解含区间数据Gamma分布参数极大似然估计的迭代公式,并应用于SARS潜伏期分布的拟合。
短句来源
  相似匹配句对
     Parameter Estimation in Gamma Distribution with Interval Data
     含区间数据Gamma分布参数估计
短句来源
     Bayesian Inference in Parameters of Gamma Distribution with Multiple Change Points
     Gamma分布参数多个转变点的Bayes推断
短句来源
     Parameter Estimation of Gamma Distribution With Ⅱ Interval Censored Data
     Ⅱ型区间数据下Gamma分布参数估计
短句来源
     Bootstraping Estimation of Parameters for Gamma Distribution
     Gamma分布的Bootstrap估计
短句来源
     Estimation of the Parameters of the Gamma Distribution
     Γ分布参数估计
短句来源
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  gamma distribution parameter
Gamma distribution parameter estimation for field reliability data with missing failure times
      
The gamma distribution parameter estimated from the data set was 0.71 0.04, and the log-likelihood of the tree was 19,510.8.
      
The number of relative substitution rate categories was set to 4 with gamma distribution parameter equal to 1.
      


In this paper, a sufficient and essential condition of admissible estimators is given with estimator (a1 X1,……,ap Xp ) of parameter a in the Gamma distribution and weighing

本文给出了Gamma分布参数α的估计量(α_1X_1,…,αX)′在加权平方和损失函数下为可容许估计的充分必要条件,获得了在一般损失函数L_v下它为可容许估计的充分条件(在线性估计类中)。

By the characteristic function and its properties,the few important theorms about Gamma distribution's numerical charateristics such as mean,variance and moment ect.are simply proved.In addition,the problem of parameter estimation are discussed,when the shape parameter α is known,the asymptotic effective estimation to the scale parameter λ is given as λ^=(nα-1)/∑ni=1X i,and the efficiency e n is provided by e n=1-2nα.

利用特征函数及其性质 ,给出Gamma分布的数字特征的几个重要定理的证明 .同时 ,讨论了Gamma分布的参数估计问题 ,在形状参数α已知的条件下 ,给出尺度参数λ的一个渐近有效估计λ^ =(nα -1) / ∑ni=1xi,其效率en =1- 2nα .

Weather generator is an important tool in studying impacts of weather/climate on a variety of systems including ecosystem and risk assessment. The purpose of this work is to develop a weather generator for applications in China. The focus is on precipitation simulation since determination of other weather variables such as temperature is dependent on precipitation simulation. A framework of first order Markov Chain with Gamma Distribution for daily precipitation is adopted in this work. Based on this framework...

Weather generator is an important tool in studying impacts of weather/climate on a variety of systems including ecosystem and risk assessment. The purpose of this work is to develop a weather generator for applications in China. The focus is on precipitation simulation since determination of other weather variables such as temperature is dependent on precipitation simulation. A framework of first order Markov Chain with Gamma Distribution for daily precipitation is adopted in this work. Based on this framework four parameters for precipitation simulation for each month at 672 stations all over China are determined using daily precipitation data from 1961 to 2000. Compared with previous works, our estimation for the parameters is made for more stations and longer observations, which makes the weather generator more applicable and reliable. The spatial distribution of the four parameters is analyzed in a regional climate context. The seasonal variation of the parameters at five stations representing regional differences is discussed. Based on the estimated monthly parameters at the 672 stations, daily precipitations for any period of time can be simulated. A 30 year simulation is made and compared with observations during 1971-2000 in terms of annual and monthly statistics.

天气发生器是气候影响评价研究的重要工具,在气候变化、地球生态系统及极端气候事件发生的风险分析等方面有着广泛的应用。为了建立一个适用于中国广大地区的天气发生器,需要对各种模拟模型及其参数的估计进行深入的研究。其中降水的模拟及其参数的估计是关键,因为气温、辐射等其他气候要素的模拟依赖于降水的发生。本文重点介绍了常用的随机降水模拟模型:两状态一阶马尔科夫链和两参数GAMMA分布。根据中国672个气象站点1961~2000年的逐日降水资料,计算了降水转移概率P (WD)、P (WW) 及GAMMA分布参数ALPHA和BETA,并分析了4个参数在中国各地的空间分布特征与不同地区各参数的季节分布特征。最后根据各地不同月份计算的四个降水模拟参数对中国各地的逐日降水进行模拟,并利用1971~2000年的实测数据对30年模拟结果在统计意义上进行了检验,模拟结果较好。

 
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