1) generalized diagonal ridge estimates
广义对角岭型估计类
1.
We put forward a generalized diagonal ridge estimates for the ridge regression coefficients.
提出了具有岭型形式的一类回归系数的参数估计——广义对角岭型估计类。
2) generalized ridge estimation
广义岭型估计
1.
Lesser components and generalized ridge estimation;
非主成份与广义岭型估计
3) ridge type generalized inverse regression estimator
岭型广义逆估计
1.
Starting from the LS regression estimation,a new biased estimator of regression coefficients called ridge type generalized inverse regression estimator is generated combining the singular value decomposition expression of the design matrix and the ordinary ridge regression estimation methods.
从LS估计出发 ,基于设计阵的奇异值分解式 ,应用岭估计方法 ,构造了回归系数的一个新的有偏估计———岭型广义逆估计 。
4) Liu-type generalized ridge estimator
Liu型广义岭估计
1.
Based on it,Liu-type generalized ridge estimator has been put forward,which can improve the ill-conditioned equations without increasing the bias.
然后就岭估计会使估值偏差增大的问题,在Liu估计的基础上,推导出一种新的有偏估计方法——Liu型广义岭估计,并给出该方法的模型、解式。
5) 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。
6) generalized ridge estimate
广义岭估计
1.
In this paper,the relations between generalized ridge estimate of classical linear model and generalized ridge estimate of data detection model are given.
建立了经典线性模型回归系数的广义岭估计和数据删除模型的广义岭估计之间的关系式,同时得出了一些相应的结论,即引入二范数度量来度量两个估计量之间差异的大小。
2.
In the paper,the singular values decomposition method is used to obtain some further conclusions on generalized ridge estimates class.
采用奇异值分解,得出了广义岭估计类F的相关性质,并用极小化均方误差的无偏估计法、Hemmerle-Brantle估计法,以及Q(c)准则讨论了岭参数阵K的选取。
3.
We proved β*c(K) was an admissible estimate,applying the idea of James Stein regression on this class of biased estimation,and proved the new estimate superior to generalized ridge estimate.
在线性回归模型Y=Xβ+ε;Ε(ε)=0;cov(ε)=σ2I下给出了有偏估计βc*(K)=(cXTX+ΦKΦT)-1XTY,其中c≥1,K=diag(k1,k2,…,kn)为对角阵,ki≥0,讨论了这种有偏估计的可容许性,利用Stein式压缩技术说明在均方误差意义下它优于广义岭估计,推广了有关结果。
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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参考词条