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instrumental variables
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  辅助变量
     First it gives analysis and comparison to Least Squares, Weighted LeastSquares, Extended Least Squares and Instrumental variables, then analysestheoretically the problems of how to realize the identification in computer.
     首先对普通最小二乘法、加权最小二乘法、增广最小二乘法和辅助变量法进行阐述、比较和分析,并理论上分析电液伺服控制系统辨识的计算机实现问题。
短句来源
     This paper studies the problem of estimating parameters of ARMA(p,q) with the observed data corrupted by an unknown white noise. A modified recursive instrumental variables(RIV) method is developed to provide consistent estimates for the parameters of AR(p) and variance of the white noise. With these obtained results, estimates of the parameters in MA(q) can be determined by using the welldeveloped Newton-Raphson algorithm.
     本文研究了如何利用受白色噪声污染的观测数据辨识ARMA(p,q)模型参数据的问题,提出了一种递推辅助变量法.利用这种方法首先辨识出AR(P)部分的参数及观测噪声的方差,然后根据所得的估计利用常用的Newton-Raphson方法确定MA(q)部分的参数.
短句来源
     The instrumental variables are obtained from predictions based on past three bearing measurements and are therefore independent of the present noisy measurements, so a recursive, unbiased estimator is established.
     利用现时刻之前的方位测量构造现在方位的预测值 ,形成了与现在测量方位在统计上独立的辅助变量 ,该辅助变量用以对拟线性估计算法的修正 ,能产生无偏的目标参数估计
短句来源
     In the proposed method,proper instrumental variables are constructed to suppress the effects of noise on the detection performance,and a useful criterion for detection is derived based on the asymptotical analysis of the orthogonality between signal and noise subspace.
     构造适当的辅助变量减轻甚至消除噪声对检测性能的影响. 对信号子空间和噪声子空间的正交性进行了分析得出新的估计准则.
短句来源
     A new method of the instrumental variables is presented based on the research of the current Pseudo-linear estimator(PLE). The simulation result of Cramer-Rao lower bound(CRLB) and root mean square error(RMSE) is obtained after the computer simulation. The algorithm is recursive, unbiased, and stable.
     在研究现有伪线性算法的基础上,新提出一个辅助变量构造的方法,并且进行仿真计算,比较了 Cramer-Rao误差下限CRLB和均方误差的仿真结果,结果表明,提出的伪线性辅助变量算法具有全局的稳定性,能够得到系统的无偏估计,可以实现递推估计。
  工具变量
     Combining local linear estimation method for nonparametic regression models with traditional estimation method for linear and nonlinear simultaneous equation model,this paper presents local linear estimators by instrumental variables with variable bandwidth for every structural equation in nonparametric simultaneous equation models and applies it to nonparametric macroeconomics simultaneous equation models in china.
     本文将非参数回归模型的局部线性估计方法与传统联立方程模型估计方法相结合 ,首次提出了非参数计量经济联立模型的局部线性工具变量变窗宽估计并应用于我国宏观经济非参数联立模型。 结果表明 :我国宏观经济非参数联立模型优于线性联立模型且线性模型将造成不必要的人为设定误差 ;
短句来源
     An Empirical Analysis of the Effect of Monetary-Policy Instrumental Variables in China
     我国货币政策工具变量效应的实证分析
短句来源
     Further, we use variance decomposition technology to examine the contribution-rate to the fluctuation of GDP caused by the shock of different instrumental variables.
     同时利用方差分解技术 ,考察不同货币政策工具变量冲击对国内生产总值GDP的影响及其贡献率的大小。
短句来源
     Local linear estimation with instrumental variables for non-parametric simultaneous equations econometric model
     非参数计量经济联立模型的局部线性工具变量估计
短句来源
     By introducing Instrumental Variables,this method can transfer data collected by the metrics tool to inputs of one cost estimation model automatically.
     该方法通过引入统计理论中的工具变量,将度量工具所采集的度量元数据自动转换为软件成本估算模型的输入。
短句来源
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  “instrumental variables”译为未确定词的双语例句
     Single stationary observer bearings-only tracking using instrumental variables
     使用辅助变量的单静止站纯方位目标跟踪
短句来源
     Modification of biased target parameter estimation for static single bearings-only observer by instrumental variables
     辅助变量法消除纯方位目标运动参数估计偏倚
短句来源
     Modification of Biased Estimation for Static Single Bearings-only Observer by Instrumental Variables
     辅助变量法消除估计偏倚的验证
短句来源
     A Single Platform Bearings-only Target Tracking Algorithm Using Instrumental Variables
     一种使用辅助变量的单站纯方位目标跟踪算法
     Inorder to discover the relationship between occupation stress and occupation task,individual coping style, the author constructed measurement error models byusing instrumental variables.
     采用辅助变量的方法建立测量误差模型,对职业紧张与职业任务及个体应对能力的关系进行分析,并对测量误差的作用进行分析。
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  instrumental variables
We estimate a panel data work hours equation by instrumental variables in an effort to resolve the puzzle and to shed light on self-employed labor supply behavior.
      
No study, however, has attempted to build up and extend results using an innovative instrumental variables (IV) model recently developed by Duncan and Leigh.
      
Union wage premiums in an instrumental variables framework
      
The authors also study the possible existence of endogeneity by using instrumental variables estimation.
      
The instrumental variables' estimates indicate that the greater the extent of federal deposit insurance coverage, the higher the bank failure rate.
      
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The identification of physical and modal parameters of damping and stiffness varying systems was examined by utilizing the differential equation model with varying physical parameters. Compared with the difference equation model, the differential equation model with varying physical parameters can considerably improve the damping identification accuracy by the Least Squares technique. On-line versions of three time domain system identification algorithms- Least Squares, Double Least Squares and Instrumental...

The identification of physical and modal parameters of damping and stiffness varying systems was examined by utilizing the differential equation model with varying physical parameters. Compared with the difference equation model, the differential equation model with varying physical parameters can considerably improve the damping identification accuracy by the Least Squares technique. On-line versions of three time domain system identification algorithms- Least Squares, Double Least Squares and Instrumental Variables, were implemented in order to determine the accuracy with which changes in the physical and modal parameters can be followed well. Data generated from various simulated time varying parameter systems, corrupted with both input and measurement noise, were used to examine the available algorithms. Comparisons were made among results obtained from the three different identification techniques. It was found-that when the noise level was increased, the best estimates on damping ratios were often obtained by the LS technique but not by the DLS and the IV techniques. When the IV approach failed, the LS approach can still give acceptable estimates.

本文利用变物理参数微分方程模型,讨论了刚度与阻尼随时间变化时,物理参数与模态参数的识别问题,比较了三种在线识别技术.数字模拟结果表明,采用变物理参数微分方程模型可比采用差分方程模型极大的提高最小二乘法识别阻尼比的精度.当加入系统的噪音较大时,有些改进识别方法失效,但最小二乘法仍能给出较好的估计.

The implementation of parameter estimation is a serious problem in the modeling for nonlinear simultaneous equations.For the estimator of best nonlinear two stage least squares(BNL2SLS)that Amemiya proposed,the procedure of selecting matrix(W)of instrumental variables is presented, which is based on the calculation of alternating conditional expectation.The algorithm of BNL2SLS estimator is explored which is recommended by two steps,and its efficiency is confirmed in simulation study.It has bred prospects...

The implementation of parameter estimation is a serious problem in the modeling for nonlinear simultaneous equations.For the estimator of best nonlinear two stage least squares(BNL2SLS)that Amemiya proposed,the procedure of selecting matrix(W)of instrumental variables is presented, which is based on the calculation of alternating conditional expectation.The algorithm of BNL2SLS estimator is explored which is recommended by two steps,and its efficiency is confirmed in simulation study.It has bred prospects to apply the algorithm proposed in this paper in practice.

ResearchfortheAlgorithmofNonlinearTwoStageLeastSquaresEstimatorZHONGDenghua;WANGRenchao;LIUBao;ZHANGShiying(TianjinUniversity...

This paper studies the problem of estimating parameters of ARMA(p,q) with the observed data corrupted by an unknown white noise. A modified recursive instrumental variables(RIV) method is developed to provide consistent estimates for the parameters of AR(p) and variance of the white noise. With these obtained results, estimates of the parameters in MA(q) can be determined by using the welldeveloped Newton-Raphson algorithm.

本文研究了如何利用受白色噪声污染的观测数据辨识ARMA(p,q)模型参数据的问题,提出了一种递推辅助变量法.利用这种方法首先辨识出AR(P)部分的参数及观测噪声的方差,然后根据所得的估计利用常用的Newton-Raphson方法确定MA(q)部分的参数.

 
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