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unbiasedness相关的网络例句

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

Some small sam-ple and large sample superiority of this estimate such as the unbiasedness,convergence,asymptotic normality and the property of simulation,are obtained.

我们得到分块拟回归的小样本和大样本性质,如无偏性、均方收敛性、强收敛性和渐近正态性,并讨论了曲线拟合的性质。

The properties of four factorized chi-square forms, which are used in minimization of correlated data, are studied, including their biasness and unbiasedness.

研究了关联实验数据的四种因子化形式的χ2 表达式及其极小化性质,同时讨论了极小化估计值的有偏性与无偏性。

To the problem of unbiasedness of L 1 estimation,basing on uniqueness of solution,Zhou Shijiang proved it according to dual theorem of linear programming; and Wang Zhizhong proved it according to probability statistics theorem by using the method from special to general; also,basing on error distribution theorem and probability statistics theorem,the authors proved it.

对于L1 估计的无偏性问题,周世健基于解法的惟一性,根据线性规划的对偶理论,证明了L1 估计的无偏性[5] ;王志忠根据数理统计理论,采用由特殊情形推广到一般情形的方法,证明了L1 估计的无偏性[6] 。

First,we deprived probability density of median closely according to probability density formula of Laplace distribution,from general to special; then we proved the unbiasedness of L 1 estimation according to probability density of median.

笔者基于误差分布理论及概率统计理论,由Laplace分布的概率密度函数公式出发,采用由一般情形到特殊情形的推理方法,严密地推导

For some parametric estimation, whether it is the best estimation or not, its consistency, unbiasedness, effectiveness, invariance, and so on are often discussed. Then, it is compared with the data we get from experiment, and the deviation with the experimental data is considered.

某一参数估计是否是"最优"估计,通常要从一致性、无偏性、有效性、不变性等方面进行讨论,进而通过实际的观察对其进行数据拟合,分析其相对于实际模型的偏差程度。

In order to think about unbiasedness, we need to rewrite our estimator in terms of the population parameter

为了考虑无偏性,我们需要用总体的参数改写

This is a globally optimized algorithm and can derive a rheological parameter estimation, showing superior statistic features including near unbiasedness of fitting residual error and almost least variance.

新算法是一个全局优化算法,所得到的流变参数估计具有拟合残差近似无偏性和方差几乎为最小的特征。

This new algorithm can derive a rheological parameter estimation that shows superior statistic features of fitting residual error unbiasedness and least variance.

该算法不需要人工给定迭代初始值,迭代过程稳定收敛到最小点,不会陷入极小点陷阱,收敛速度很快,所得到的流变参数估计具有拟合残差无偏性和方差最小的优良统计特征。

We begin by establishing the unbiasedness of OLS under a set of assumptions.

首先,我们在一些假定下证明OLS的无偏性。

There is no effect on the unbiasedness of the OLS estimators.

过度设定对我们的参数估计没有影响,OLS仍然是无偏的。

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