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Identification of delayed system using instrumental variable method

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控制理论与应用（英文版） 2012年第3期10卷 380-384页

作者： Dalvinder KAUR Lillie DEWAN Electronics and Instrumentation Department TITS BhiwaniMD University RohtakHaryanaIndia Electrical Engineering Department NIT KurukshetraHaryanaIndia

System identification uses system inputs and outputs to raise mathematical models. Various techniques of system identification exist that offer a nominal model and an uncertainty bound. Many practical systems such as thermal processes ＆ chemical processes have inbuilt time delay. If the time delay used in the system model for controller design does not concur with the actual process time delay, a closed-loop system may be unstable or demonstrate unacceptable transient response characteristics so here the time delay is assumed to be time-invariant. This paper proposes on-line identification of delayed complex/uncertain systems using instrumental variable （IV） method. Parametric uncertainty has been considered which may be represented by variations of certain system parameters over some possible range. This method allows consistent estimation when the system parameters are associated with the noise terms, as the IV methods （IVM＇s） usually make no assumption on the noise correlation configuration. The faster convergence of the parameters including noise terms has been proved in this paper. Iterative prefiltering （IP） method has also been used for the identification of the delayed uncertain system and the graphical results given in this paper demonstrate that the convergence results are inferior to the instrumental variable method.

关键词： Parametric uncertainty Time delay Sequential nonlinear instrumental variable Iterative prefiltering

An instrumental variable approach to unveiling the determinants of flatted factory rent in Hong Kong

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Economic and Political Studies 2020年第1期8卷 115-138页

作者： Alex Wing Ho Yiu Terence Tai Leung Chong Department of Economics The Chinese University of Hong KongHong Kong SARChina Lau Chor Tak Institute of Global Economics and Finance The Chinese University of Hong KongHong Kong SARChina

The early period of industrialisation in the Hong Kong SAR occurred during the 1950s–*** were engaged in labour-intensive manufacturing processes with the assistance of machines in factory *** the 1980s,manufacturers in Hong Kong have faced keen competition from neighbouring economies,amidst the rising costs of land and ***,since the adoption of an opening-up policy by the Chinese mainland since 1978,more and more local manufacturers in Hong Kong have relocated their production processes to the mainland so as to take advantage of the lower factor *** a result,the contribution of the manufacturing sector to GDP declined from around 20%in 1986 to 2.7%in 2006 and further decreased to merely 1.1%in ***,there has been a general upward trend of real flatted factory1 rent in Hong Kong in the past *** study,via a threshold regression,demonstrates that not only demand from the retail property rental market has been a factor in the increase of factory rent,but demands from the office rental market and local households have also contributed to the recent rise in real factory rent since 2006 Q1.

关键词： Factory rent retail property rent office rent tourism instrumental variable

Layoff Factors Analysis:Evidence from 2021 China General Social Survey

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Proceedings of Business and Economic Studies 2024年第4期7卷 183-194页

作者： Zheng Ji Chongtao Zhao University of Toronto TorontoONM5S 1A1Canada

This paper analyzes factors that explain company layoffs,given the individual layoff data in 2021,*** the Probit regression model,we find that gender inequality exists in layoffs,an employee’s work experience becomes less critical in the company’s layoff decisions,and how an employee’s health reasons affect work affects its probability of being laid *** we consider a significant endogeneity issue with education,using parents’education as an instrumental variable suggests that political status cannot be a significant advantage for employees to lower the chance of being laid ***,evidence implies that policymakers encouraging the pursuit of higher educational degrees can foster stability in the labor market.

关键词： Layoff Education instrumental variable Probit model

Impact of air pollution on urbanization:evidence at China’s city level

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Chinese Journal of Population,Resources and Environment 2024年第3期22卷 268-274页

作者： Yanchun Yi Yixin Geng Jiawen Wu Yinling Liu School of Economics&Management Huzhou CollegeHuzhou 313000China School of Economics and Management Hubei Normal UniversityHuangshi 435002China

This paper investigates the effect and transmission mechanism of air pollution on urbanization based on data from China’s 107 cities during 2005–*** order to identify the impact of air pollution on China’s urbanization,we utilized night light data to represent the level of urbanization and used temperature inversion as an instrumental variable to mitigate endogeneity within the two-stage least squares *** results suggest that air pollution significantly slowed China’s urbanization process with economic growth acting as the transmission *** heterogeneity analyses revealed that air pollution had a greater negative impact on urbanization in northern regions than that in southern regions,and a greater negative impact in resource-oriented cities than that in non-resource-based *** also find that air pollution was to the detriment of urbanization in larger cities,which have more than 3 million residents,while it did not have a significant impact on Type II large cities,which have fewer than 3 million residents.

关键词： Air pollution Urbanization Influencing mechanism 2SLS Night light data instrumental variable

ESTIMATION AND INFERENCE FOR VARYING-COEFFICIENT REGRESSION MODELS WITH ERROR-PRONE COVARIATES

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Journal of Systems Science & Complexity 2014年第6期27卷 1263-1285页

作者： XU Yongqing LI Xiaoli CHEN Gemai School of Statistics and Management Shanghai University of Finance and Economics Department of Mathematics & Statistics University of CalgaryCalgaryAlberta T2N1N4Canada

This paper studies the estimation and inference for a class of varying-coefficient regression models with error-prone *** authors focus on the situation where the covariates are unobserved,there are no repeated measurements,and the covariance matrix of the measurement errors is unknown,but some auxiliary information is *** authors propose an instrumental variable type local polynomial estimator for the unknown varying-coefficient functions,and show that the estimator achieves the optimal nonparametric convergence rate,is asymptotically normal,and avoids using undersmoothing to allow the bandwidths to be selected using data-driven methods.A simulation is carried out to study the finite sample performance of the proposed estimator,and a real date set is analyzed to illustrate the usefulness of the developed methodology.

关键词： Error-prone covariate instrumental variable local polynomial efficient estimation varying-coefficient.

A closed-form solution for moving source localization using LBI changing rate of phase difference only

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Chinese Journal of Aeronautics 2014年第2期27卷 365-374页

作者： Zhang Min Guo Fucheng Zhou Yiyu College of Electronic Science and Engineering National University of Defense Technology

Due to the deficiencies in the conventional multiple-receiver localization syste,.ns based on direction of arrival （DOA） such as system complexity of interferometer or array and ampli- tude/phase unbalance between multiple receiving channels and constraint on antenna configuration, a new radiated source localization method using the changing rate of phase difference （CRPD） measured by a long baseline interferometer （LBI） only is studied. To solve the strictly nonlinear problem, a two-stage closed-form solution is proposed. In the first stage, the DOA and its changing rate are estimated from the CRPD of each observer by the pseudolinear least square （PLS） method, and then in the second stage, the source position and velocity are found by another PLS minimiza- tion. The bias of the algorithm caused by the correlation between the measurement matrix and the noise in the second stage is analyzed. To reduce this bias, an instrumental variable （IV） method is derived. A weighted IV estimator is given in order to reduce the estimation variance. The proposed method does not need any initial guess and the computation is small. The Cramer-Rao lower bound （CRLB） and mean square error （MSE） are also analyzed. Simulation results show that the proposed method can be close to the CRLB with moderate Gaussian measurement noise.

关键词： Changing rate of phase dif-ference Cramer-Rao lower bound Estimation bias instrumental variable Least square Long baseline interferome-ter Radiated source localization

Empirical Likelihood Inference for the Semiparametric Varying-Coefficient Spatial Autoregressive Model

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Journal of Systems Science & Complexity 2021年第6期34卷 2310-2333页

作者： LUO Guowang WU Mixia PANG Zhen College of Big Data Statistics Guizhou University of Finance and EconomicsGuiyang 550025China College of Statistics and Data Science Faculty of ScienceBeijing University of TechnologyBeijing 100124China Department of Applied Mathematics Hong Kong Polytechnic UniversityHong KongChina

In this paper empirical likelihood(EL)-based inference for a semiparametric varyingcoefficient spatial autoregressive model is *** maximum EL estimators for the parametric component and the nonparametric component are ***,asymptotic properties of the proposed estimators and EL ratios are derived,and the corresponding confidence regions/bands are *** finite sample performances are studied via simulation and an example.

关键词： Confidence regions empirical likelihood instrumental variable residual-adjusted Wilks theorem

Mendelian randomization and pleiotropy analysis

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Quantitative Biology 2021年第2期9卷 122-132页

作者： Xiaofeng Zhu Department of Population and Quantitative Health Sciences School of MedicineCase Western Reserve UniversityClevelandOH 44106USA

Background:Mendelian randomization(MR)analysis has become popular in inferring and estimating the causality of an exposure on an outcome due to the success of genome wide association *** statistical approaches have been developed and each of these methods require specific ***:In this article,we review the pros and cons of these *** use an example of high-density lipoprotein cholesterol on coronary artery disease to illuminate the challenges in Mendelian randomization ***:The current available MR approaches allow us to study causality among risk factors and ***,novel approaches are desirable for overcoming multiple source confounding of risk factors and an outcome in MR analysis.

关键词： Mendelian randomization causality summary statistics confounding instrumental variable

On the use of kernel machines for Mendelian randomization

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Frontiers of Electrical and Electronic Engineering in China 2017年第4期5卷 368-379页

作者： Weiming Zhang Debashis Ghosh Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado Anschutz MedicalCampus Aurora CO 80045 USA

Background： Properly adjusting for unmeasured confounders is critical for health studies in order to achieve valid testing and estimation of the exposure＇s causal effect on outcomes. The instrumental variable （IV） method has long been used in econometrics to estimate causal effects while accommodating the effect of unmeasured confounders. Mendefian randomization （MR）, which uses genetic variants as the instrumental variables, is an application of the instrumental variable method to biomedical research fields, and has become popular in recent years. One often-used estimator of causal effects for instrumental variables and Mendelian randomization is the two-stage least square estimator （TSLS）. The validity of TSLS relies on the accurate prediction of exposure based on IVs in its first stage. Results： In this note, we propose to model the link between exposure and genetic IVs using the least-squares kernel machine （LSKM）. Some simulation studies are used to evaluate the feasibility of LSKM in TSLS setting. Conclusions： Our results show that LSKM based on genotype score or genotype can be used effectively in TSLS. It may provide higher power when the association between exposure and genetic IVs is nonlinear.

关键词： Mendelian randomization kernel machine instrumental variable unmeasured confounder casual inference