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1)  Generalized c-K estimators
广义c-K估计
1.
Aiming at the fundamental reason for the bad performance of the LS estimator of the coefficients in the linear regression models,presents the generalized c-K estimators of the coefficients,which combines various classical biased estimators into a bigger class of estimators and studies the improvement of the biased estimators.
针对引起线性回归模型LS估计性能变坏的根本原因,提出了回归系数的广义c-K估计,将众多经典的有偏估计结合在一起,对有偏估计的改进进行研究。
2.
Aiming at the fundamental reason for the bad performance of the LS estimator of the coefficients in the linear regression models,this paper presents the generalized c-K estimators of the coefficients,which combines various classical biased estimators into a bigger class of estimators and studies the improvement of the biased estimators.
针对引起线性回归模型LS估计性能变坏的根本原因,提出了回归系数的广义c-K估计,将众多经典的有偏估计结合在一起,对有偏估计的改进进行了研究,分别证明了最小化均方误差和数量化矩阵K均可对Stein估计进行改进,给出了参数的最优值,为病态线性回归模型系数有偏估计的改进提供了有效途径。
2)  c-k class of estimators
c-k型估计
1.
In the light of the essence of the ill condition in the linear regression model, this paper first proposes the c-k class of estimators of the coefficients, which combines the ridge regression estimators and the Stein shrinkage estimators into a bigger class of estimators.
针对线性回归模型病态的根本原因,提出了一类新的估计———c-k型估计,将岭估计与Stein估计统一到一个估计类;研究了这一估计类,证明利用岭回归技术可以改进著名的Stein估计(在均方误差意义下);同时研究了相应参数的最优值,分别给出了它的一个上界及下界,为病态线性回归模型系数的有偏估计提供了改进的技术途径。
3)  generalized k-nearest neighbor
广义k-最近邻估计
1.
The non-parametric density estimation—generalized k-nearest neighbor(GKNN) estimation based novel independent component analysis(ICA) algorithm which is fully blind to the sources is proposed using a linear ICA neural network.
基于概率密度非参数估计的广义k-最近邻估计(GKNN)和线性独立成分分析(ICA)神经网络,提出了一种新的ICA非参数算法,实现了对源信号分布的全"盲"要求。
4)  c-(K,S) class of estimators
c-(K,S)型估计
1.
The paper first proposes the c-(K,S) class of estimators of the coefficients.
提出一类新的估计——c-(K,S)型估计,证明了在均方误差意义下运用泛岭回归技术可以改进S te in的SLS估计,同时给出了参数的最优值满足的条件。
5)  c-k improved estimators
c-k型改进估计
6)  generalized ridge estimation
广义岭估计
1.
Two criterions for the determination of partial parameter of multivariate generalized ridge estimation;
多元广义岭估计确定偏参数的两种准则
2.
This paper combined bundle adjustment with line and angle respectively computing,generalized ridge estimation and indirect adjustment of observation with condition.
CCD卫星影像空间后方交会时,存在系数矩阵列向量间的强相关的问题,用光束法平差同样存在这个问题,将光束法平差与线角元素分求法、广义岭估计、附有限制条件的平差结合,证实三种方法都可以克服平差时外元素和变率改正数震荡大的缺点,并且取得了合理的空间后方交会精度和地面点定位精度。
3.
In this paper the criterion is generalized and then used to compare the advantage and disadvantage of the least square estimation of the regression parameter in growth curve model and a generalized ridge estimation.
本文将它推广应用于生长曲线模型回归参数阵的最小二乘估计和广义岭估计优劣性的比较。
补充资料:广义
范围较宽的定义(跟‘狭义’相对):~的杂文也可以包括小品文在内。
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