英语翻译Numerical results from the application of the parameters-matching methods on the data appear in table 4,while the graphs for the corresponding Gamma densities are compared against the histograms in figures 4(a),(b) and 5(a),(b).(In these

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英语翻译Numericalresultsfromtheapplicationoftheparameters-matchingmethodsonthedataappearintable4,whileth

英语翻译Numerical results from the application of the parameters-matching methods on the data appear in table 4,while the graphs for the corresponding Gamma densities are compared against the histograms in figures 4(a),(b) and 5(a),(b).(In these
英语翻译
Numerical results from the application of the parameters-matching methods on the data appear in table 4,while the graphs for the corresponding Gamma densities are compared against the histograms in figures 4(a),(b) and 5(a),(b).(In these figures,the curve for the LVMAX fit is the one,which,by design of the method,tracks exactly the histogram’s peak.) Somewhat surprisingly,the best results were obtained for the two terminals of case 1,i.e.,those corresponding to histograms of a somewhat ‘irregular shape.Indeed,the contents of table 3 show that,for case 1,the three sets of parameters values are close to each other and that the mean and variance corresponding to the Gamma densities resulting from LVMAX and C-LVMAX are close to the sample counterparts.Furthermore,the parameter values for the two terminals are close enough to allow a single model for the description of both histograms and this fact provides another bit of evidence towards the statistical identity of the traffic profiles from all terminals in a videoconferencing session.Note,however,that this invariance is not carried over to the histograms corresponding to different sessions over the same MCU mode but with a differing number of terminals,as the histograms of case 1 (MCU mode 3 with two terminals) are significantly different from the histogram of case 2 (MCU mode 3
with four terminals) and the same holds for the corresponding sample means and variances.

英语翻译Numerical results from the application of the parameters-matching methods on the data appear in table 4,while the graphs for the corresponding Gamma densities are compared against the histograms in figures 4(a),(b) and 5(a),(b).(In these
数值结果从应用的参数匹配方法的数据显示在表4,而相应的伽马密度的图是针对数字4的直方图比较(一),(b)和5(1),(二).(在这些数字,为LVMAX拟合曲线就是一个,其中,由该方法的设计,跟踪正是直方图的高峰期.)出人意料的是,
最好的结果为1的情况,即那些对应有点'不规则shape.Indeed直方图,表3显示的内容,两个码头,对于案件1,参数值接近,3套其他,而相应的均值和方差的伽马密度从LVM的产生
斧和C - LVMAX接近样本对应.此外,这两个码头的参数值足够接近,以便为双方的直方图,这一事实说明单一的模式提供了另一个证据,实现从视频会议会话中的所有终端的交通概况统计的身份位.但是请注意,这不是不变性结转到在同一个微控制器模式的直方图对应不同的会议,但有一些不同的终端,如例1(单片机模式两个码头3)直方图明显来自不同直方图例2(单片机模式3
拥有四个终端)和同样适用于相应的样本均值和方差.

数值结果从应用的参数匹配方法的数据显示在表4,而相应的伽马密度的图是针对数字4的直方图比较(一),(b)和5(1),(二)。 (在这些数字,为LVMAX拟合曲线就是一个,其中,由该方法的设计,跟踪正是直方图的高峰期。)出人意料的是,
最好的结果为1的情况,即那些对应有点'不规则shape.Indeed直方图,表3显示的内容,两个码头,对于案件1,参数值接近,3套其他,而相应的均值和方差的伽...

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数值结果从应用的参数匹配方法的数据显示在表4,而相应的伽马密度的图是针对数字4的直方图比较(一),(b)和5(1),(二)。 (在这些数字,为LVMAX拟合曲线就是一个,其中,由该方法的设计,跟踪正是直方图的高峰期。)出人意料的是,
最好的结果为1的情况,即那些对应有点'不规则shape.Indeed直方图,表3显示的内容,两个码头,对于案件1,参数值接近,3套其他,而相应的均值和方差的伽马密度从LVM的产生
斧和C - LVMAX接近样本对应。此外,这两个码头的参数值足够接近,以便为双方的直方图,这一事实说明单一的模式提供了另一个证据,实现从视频会议会话中的所有终端的交通概况统计的身份位。但是请注意,这不是不变性结转到在同一个微控制器模式的直方图对应不同的会议,但有一些不同的终端,如例1(单片机模式两个码头3)直方图明显来自不同直方图例2(单片机模式3
拥有四个终端)和同样适用于相应的样本均值和方差。

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