抗差估计等价权函数中临界值一般定为常数。
Critical values of the equivalent weight function are often fixed in constants in robust estimation.
抗差估计与最小二乘估计在相应条件下各具优点。
Robust and least squares estimators have their own merits and demerits in corresponding conditions.
抗差m估计是使用最广泛、计算较简明的抗差估计法。
Robust m estimation is widely used for its robustness and simple calculation procedure.
文中主要介绍了利用误差分布律概率密度函数定权来进行抗差估计的一种方法。
An introduction is Made of the method of using the weight of probability density function of error distribution law to conduct anti-error estimation.
抗差估计等价权函数一般由正态分布统计量构造，其临界值（或称准则）一般由实际经验确定。
The equivalent weight function in robust estimation is usually constructed by the statistics of normal distribution. The critical values are often fixed by experience.
零误差实验可以更有效地观察粗差在经过抗差估计以后的分布情况，再将估计值与真值比较，从而较客观地对各种抗差估计方法做出评价。
Zero-error experiment can observe the distribution of gross error after robust estimation, then compare the estimation value and real value, so we can evaluate externally all kinds of robust method.
为此，采用崩溃率为20%、附有条件的抗差最小二乘法估计马斯京根汇流参数最优值。
Therefore, the robust least square method with some additional conditions at the breakdown ratio being 20% was employed for optimal estimation of Muskingum parameters.
通过使用模拟数据进一步验证了稳健估计用于参数估计中良好的抗差作用。
By simulation test, it shows that robust estimation, which is applied to parameter estimation, can resist gross errors.
针对卫星精密定轨过程中观测资料存在粗差以及观测资料的合理定权问题，将抗差方差分量估计引入到卫星精密定轨中。
In this paper, the robust variance component estimation is introduced into the satellite orbit determination to resist the effects of outlying observations and to determine the weights.
结果表明：抗差主成分估计不仅可以解除法方程系数降的病态，而且对于抑制观测粗差的影响也有显著功效。
The results show that the robust principal component estimation can not only overcome the ill condition of the normal equation. but also resist the outlier effects to the model parameters.
结果表明：抗差主成分估计不仅可以解除法方程系数降的病态，而且对于抑制观测粗差的影响也有显著功效。
The results show that the robust principal component estimation can not only overcome the ill condition of the normal equation. but also resist the outlier effects to the model parameters.
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