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GED相关的网络例句
与 GED 相关的网络例句 [注:此内容来源于网络,仅供参考]

In autoregression models, when the parameter from GED is known, adaptive rejection sampling method is used to estimate parameters; when the parameter from GED is unknown, we have to decide a range, also use the same method to give a reasonable estimate of the parameters.

在自回归模型中,GED分布的参数已知的情况下,基于似然函数的形式用拒绝抽样方法估计自回归系数;GED分布的参数未知时,我们给定参数的范围,用拒绝抽样方法寻找自回归系数合理的估计值。

He stood quite still, while the light of Ged's approach brightened on his eyeless face.

他很安静地站着,Ged法杖上的光渐渐靠近照亮了他没有眼睛的脸。

"I am named Ged. And you?"

"我叫Ged,你呢?"

"Maybe we did not seek it," said Ged.

"或许那不是我们人所追求的。"Ged说。

Speaking his thought, Ged said,"We have come too far to turn back."

Ged说出了他的心事,"我们已经走得太远,不能回头了。"

Ged said nothing, but he stood up.

Ged没有说话,但他站了起来。

He stood still, there in the narrow valley in the dark, and Ged stood still beside him.

他静静地站在狭长的山谷的黑暗中,Ged依然在他的身旁。

"My name is no use to you," Ged said. You have no power over me at all.

"我的真名对你一无用处,"Ged说,你根本没有打倒我的力量。

The results of research show GED can display features-tailed more exactly than student's t distribution and gauss normalized distribution. Meanwhile, two models of EGARCH and PARCH are better than others GARCH model.

实证分析结果表明,与正态分布和t分布相比,GED分布能较好的反映股市收益率回报序列的厚尾特征,同时使用GARCH类模型预测VaR值时,EGARCH和PARCH模型要优于其他模型。

In the empirical analysis part, statistical descriptions on the sample funds are made firstly, which show that the actual distribution of each sample fund"s daily net value return possesses the characteristic of leptokurtosis. So it is necessary to add student T distribution and GED to capture such leptokurtosis characteristic other than normal distribution. Secondly, ARCH test shows that there exists volatility clustering in each sample fund"s daily net value return, so GARCH related models should be used to describe such volatility clustering characteristic.

实证分析部分首先对样本基金进行统计描述,得出其收益序列均存在尖峰厚尾特征,不服从正态分布,因此有必要在下面的VaR计算中加入T分布和GED分布来捕捉这种尖峰厚尾特征;并且经ARCH检验后得出收益序列存在明显的波动聚集性的特征,因此可以选择GARCH类模型来描述这种特性,经过模型筛选,得出最适合我国开放式股票型基金的收益波动性模型为GARCH(1,1)模型。

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