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Discrete (J,J′)-Lossless Factorization
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作者 Wang Kang Zheng Hairao Qiu Wei 《Wuhan University Journal of Natural Sciences》 CAS 1999年第1期17-22,共6页
Discrete (J,J′) lossless factorization is established by using conjugation.For stable case ,the existence of such factorization is equivalent to the existence of a positive solution of a Riccati equation. For un... Discrete (J,J′) lossless factorization is established by using conjugation.For stable case ,the existence of such factorization is equivalent to the existence of a positive solution of a Riccati equation. For unstable case ,the existence conditions can be reduced to the existence of two positive solution of two Riccati equations. 展开更多
关键词 discrete (J J′) lossless factorization Riccati operator and equation
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Discrete H~∞ Control Via Conjugation
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作者 Wang Kang Zheng Huirao Qiu Wei 《Wuhan University Journal of Natural Sciences》 CAS 1999年第1期23-29,共7页
Discrete H ∞ control theory were obtained by conjugation,chain scattering representation and (J,J′) lossless factorization.The existence of the solution is equivalent to the existence of two positive s... Discrete H ∞ control theory were obtained by conjugation,chain scattering representation and (J,J′) lossless factorization.The existence of the solution is equivalent to the existence of two positive solutions of two Riccati equations. 展开更多
关键词 discrete (J J′) lossless factorization CONJUGATION chain scattering representation Riccati equation
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Returns to Lying? Identifying the Effects of MisreporUng When the Truth Is Unobserved
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作者 Yingyao Hu Arthur Lewbel 《Frontiers of Economics in China-Selected Publications from Chinese Universities》 2012年第2期163-192,共30页
Consider an observed binary regressor D and an unobserved binary vari- able D*, both of which affect some other variable Y. This paper considers nonpara- metric identification and estimation of the effect of D on Y, ... Consider an observed binary regressor D and an unobserved binary vari- able D*, both of which affect some other variable Y. This paper considers nonpara- metric identification and estimation of the effect of D on Y, conditioning on D* = 0. For example, suppose Y is a person's wage, the unobserved D* indicates if the person has been to college, and the observed D indicates whether the individual claims to have been to college. This paper then identifies and estimates the difference in av- erage wages between those who falsely claim college experience versus those who tell the truth about not having college. We estimate this average effect of lying to be about 6% to 20%. Nonparametric identification without observing D* is obtained ei- ther by observing a variable V that is roughly analogous to an instrument for ordinary measurement error, or by imposing restrictions on model error moments. 展开更多
关键词 binary regressor MISCLASSIFICATION measurement error unobserved factor discrete factor program evaluation treatment effects returns to schooling wage model
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