利用最小二乘估计对甲板的变形进行了分析。
The least squares estimation was applied to the analysis of deck deformation.
本文阐述了两类不同概念的递推最小二乘估计。
In this paper, Two Different Concepts for the Recursion of Least Square Estimation is Introduced.
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.
通过加权最小二乘估计来有效地利用系统的冗余信息。
It also makes use of systems redundant information effectively by weighted least squares estimators.
在线性回归中，常用最小二乘估计求线性方程的回归系数。
In linear regression, the least squares estimation is heavily innuenced with outlyers.
提出了基于复数U - D分解的复参数最小二乘估计方法。
The paper presents a new U-D factorization based least squares methods for complex estimation.
模拟结果表明加权最小二乘估计比最小二乘估计有优良的性质。
Simulation results show that the weighted least squares estimate has better properties than the least squares estimate.
本文就卫星测地情形，对最小二乘估计的递推算法进行误差分析。
A error analysis of the recurrent algorithm of Least Squares estimate for satellite geodesy is given in this paper.
给出了线性回归模型中的加权最小二乘估计以及最优权数的选择。
This paper gives weighted least squares estimate and the method to choose optimum weighted function for linear regression model.
本文提出了基于复数U - D分解的复参数最小二乘估计方法。
The Paper presents a new U-D factorization based least squares methods for complex estimation.
推导了利用单传感器接收信号的参数估计的最小二乘估计计算公式。
The formulas for estimating parameters were derived for signals received by a single sensor.
当平差模型中存在复共线关系时，未知参数的最小二乘估计很不可靠。
The least Square estimates are not reliable when there exists multicollinearity in adjustment model.
本文提出一种克服线性回归模型系数矩阵病态的“紧致最小二乘估计”。
In this paper a "compact least square method" is presented to overcome the ill-conditioned coefficient matrices in the linear regression models.
本文讨论回归方程组系数的估计，给出最小二乘估计是有效估计的条件。
In the present paper, We give the necessary and sufficient conditions for which the minimum variance linear unbiased estimator reduces to the least square in multivariate linear models.
本文给出了若干近似公式，以分析非线性回归模型的最小二乘估计的残差。
Several approximate formulas are given for residual analysis of the least square estimator in nonlinear regression model.
本文中给出了由脉冲响应序列值求其传递函数参数和阶的最小二乘估计方法。
In this paper, the least square estimation method is presented, in which impulse transfer function parameters and orders are derived from impulse response sequences.
已经证实本定理对解决处于闭环中全部参数同时进行最小二乘估计十分有用。
The theorem has been verified to be very useful in estimating the all parameters of controlled plant in a closed loop via least squares method.
在获得了相应的数学模型后，对最小二乘估计和最大似然估计方法进行了比较。
After deriving the mathematical equations, a comparison between the LS and the ML estimators was performed.
目的改进回归分析的经典最小二乘估计方法和探讨光滑样条非参数回归分析方法。
Objective To improve on classical least squares estimate of regression analysis and explore nonparametric smoothing spline regression analysis.
给出了当数据一步更新时，利用矩阵QR分解进行最小二乘估计的直接递推形式。
The direct form for the recursive least squares estimation via matrix QR decomposition with one step data updated is given .
在含有离群值的情况下，分析了最小二乘估计不能克服粗大误差对回归曲线的影响。
On the data including the discrete points, least square estimation can not control the strong error affecting the regression curve.
结果表明，当样本大小大于50时，回归系数的最小二乘估计具有较高的估计精度；
Our research shows that when sample size is greater than 50, the least square estimate of regression coefficiencies has high estimate precision.
对于线性模型中回归参数的最小二乘估计的研究工作已经有了系统和完整的研究结论。
The research about least square estimation of regression parameters in the linear model has included integrated and systemic results.
线性无偏最小方差估计与最优加权最小二乘估计是线性模型下两种最常用的估计方法。
The linear unbiased minimum variance estimate and the optimally weighted least squares estimate are two of the most popular estimation methods for a linear model.
若直接采用最小二乘估计的公式，因计算过程需要求矩阵的逆及乘积，计算量非常大。
If we use the equation of least square estimator directly, computing amount is often very great because course of computing need calculate the inverse of matrix and multiplication of matrix.
该方法在稳健性方面明显优于最小二乘估计，更有效地刻划了传感性输出特征的本质。
The method is obviously superior to the LSE in robustness. And the character of sensor output are effective described by the improved method.
在给定的线性模型下，讨论了最优加权最小二乘估计与线性无偏最小方差估计性能比较。
The discussion on the property comparison between optimally weighted LS estimate and linear unbiased minimum variance estimate for a linear model is presented.
根据信号相位匹配原理及其信号参数的最小二乘估计方法，提出了一种单频信号检测方法。
On the basis of signal phase matching principle and the method of least squares of parameter estimation, a method for single-frequency signal detection is presented in this paper.
主要考虑了同方差型的半参数线性回归模型中参数的随机加权最小二乘估计（RWLSE）。
The randomly weighted least square estimator (RWLSE) for the parametric component in semi-parametric regression models was mainly discussed.
主要考虑了同方差型的半参数线性回归模型中参数的随机加权最小二乘估计（RWLSE）。
The randomly weighted least square estimator (RWLSE) for the parametric component in semi-parametric regression models was mainly discussed.
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