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New Algorithm Model for Processing GeneralizedDynamic Nonlinear Data Derived from Deformation Monitoring Network
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作者 LINXiangguo LIANGYong 《Geo-Spatial Information Science》 2005年第2期133-137,共5页
The processing of nonlinear data was one of hot topics in surveying and mapping field in recent years. As a result, many linear methods and nonlinear methods have been developed. But the methods for processing general... The processing of nonlinear data was one of hot topics in surveying and mapping field in recent years. As a result, many linear methods and nonlinear methods have been developed. But the methods for processing generalized nonlinear surveying and mapping data, especially for different data types and including unknown parameters with random or nonrandom, are seldom noticed. A new algorithm model is presented in this paper for processing nonlinear dynamic multiple-period and multiple-accuracy data derived from deformation monitoring network. 展开更多
关键词 deformation monitoring generalized nonlinear data processing Marquardtmethod parameter estimate
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NONLINEAR DATA RECONCILIATION METHOD BASED ON KERNEL PRINCIPAL COMPONENT ANALYSIS 被引量:6
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作者 Yan Weiwu Shao HuiheDepartment of Automation,Shanghai Jiaotong University,Shanghai 200030, China 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2003年第2期117-119,共3页
In the industrial process situation, principal component analysis (PCA) is ageneral method in data reconciliation. However, PCA sometime is unfeasible to nonlinear featureanalysis and limited in application to nonline... In the industrial process situation, principal component analysis (PCA) is ageneral method in data reconciliation. However, PCA sometime is unfeasible to nonlinear featureanalysis and limited in application to nonlinear industrial process. Kernel PCA (KPCA) is extensionof PCA and can be used for nonlinear feature analysis. A nonlinear data reconciliation method basedon KPCA is proposed. The basic idea of this method is that firstly original data are mapped to highdimensional feature space by nonlinear function, and PCA is implemented in the feature space. Thennonlinear feature analysis is implemented and data are reconstructed by using the kernel. The datareconciliation method based on KPCA is applied to ternary distillation column. Simulation resultsshow that this method can filter the noise in measurements of nonlinear process and reconciliateddata can represent the true information of nonlinear process. 展开更多
关键词 principal component analysis KERNEL data reconciliation nonlinear
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Nonlinear Dimensionality Reduction and Data Visualization:A Review 被引量:4
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作者 Hujun Yin 《International Journal of Automation and computing》 EI 2007年第3期294-303,共10页
Dimensionality reduction and data visualization are useful and important processes in pattern recognition. Many techniques have been developed in the recent years. The self-organizing map (SOM) can be an efficient m... Dimensionality reduction and data visualization are useful and important processes in pattern recognition. Many techniques have been developed in the recent years. The self-organizing map (SOM) can be an efficient method for this purpose. This paper reviews recent advances in this area and related approaches such as multidimensional scaling (MDS), nonlinear PC A, principal manifolds, as well as the connections of the SOM and its recent variant, the visualization induced SOM (ViSOM), with these approaches. The SOM is shown to produce a quantized, qualitative scaling and while the ViSOM a quantitative or metric scaling and approximates principal curve/surface. The SOM can also be regarded as a generalized MDS to relate two metric spaces by forming a topological mapping between them. The relationships among various recently proposed techniques such as ViSOM, Isomap, LLE, and eigenmap are discussed and compared. 展开更多
关键词 Dimensionality reduction nonlinear data projection multidimensional scaling self-organizing maps nonlinear PCA principal manifold
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A Novel Robust Nonlinear Dynamic Data Reconciliation 被引量:4
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作者 高倩 阎威武 邵惠鹤 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2007年第5期698-702,共5页
Outlier in one variable will smear the estimation of other measurements in data reconciliation (DR). In this article, a novel robust method is proposed for nonlinear dynamic data reconciliation, to reduce the influe... Outlier in one variable will smear the estimation of other measurements in data reconciliation (DR). In this article, a novel robust method is proposed for nonlinear dynamic data reconciliation, to reduce the influence of outliers on the result of DR. This method introduces a penalty function matrix in a conventional least-square objective function, to assign small weights for outliers and large weights for normal measurements. To avoid the loss of data information, element-wise Mahalanobis distance is proposed, as an improvement on vector-wise distance, to construct a penalty function matrix. The correlation of measurement error is also considered in this article. The method introduces the robust statistical theory into conventional least square estimator by constructing the penalty weight matrix and gets not only good robustness but also simple calculation. Simulation of a continuous stirred tank reactor, verifies the effectiveness of the proposed algorithm. 展开更多
关键词 nonlinear dynamic data reconciliation ROBUST M-ESTIMATOR OUTLIER OPTIMIZATION
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CONSERVATIVE ESTIMATING FUNCTION IN THE NONLINEAR REGRESSION MODEL WITH AGGREGATED DATA 被引量:1
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作者 林路 《Acta Mathematica Scientia》 SCIE CSCD 2000年第3期335-340,共6页
The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When thi... The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function. 展开更多
关键词 nonlinear regression model with aggregated data quasi-score function conservative vector field potential function
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THE MIXED PROBLEM FOR A CLASS OF NONLINEAR SYMMETRIC HYPERBOLIC SYSTEMS WITH DISCONTINUOUS DATA 被引量:1
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作者 邵志强 陈恕行 《Acta Mathematica Scientia》 SCIE CSCD 2005年第4期610-620,共11页
This paper studies the nonlinear mixed problem for a class of symmetric hyperbolic systems with the boundary condition satisfying the dissipative condition about discontinuous data in higher dimension spaces, establis... This paper studies the nonlinear mixed problem for a class of symmetric hyperbolic systems with the boundary condition satisfying the dissipative condition about discontinuous data in higher dimension spaces, establishes the local existence theorem by using the method of a prior estimates, and obtains the structure of singularities of the solutions of such problems. 展开更多
关键词 nonlinear mixed problem discontinuous data symmetric hyperbolic systems
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Sampled-data Observer Design for a Class of Stochastic Nonlinear Systems Based on the Approximate Discrete-time Models 被引量:2
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作者 Xinxin Fu Yu Kang Pengfei Li 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2017年第3期507-511,共5页
In this paper,we studied the approximate sampleddata observer design for a class of stochastic nonlinear systems.Euler-Maruyama approximation was investigated in this paper because it is the basis of other higher prec... In this paper,we studied the approximate sampleddata observer design for a class of stochastic nonlinear systems.Euler-Maruyama approximation was investigated in this paper because it is the basis of other higher precision numerical methods,and it preserves important structures of the nonlinear systems.Also,the form of Euler-Maruyama model is simple and easy to be calculated.The results provide a reference for sampled-data observer design method for such stochastic nonlinear systems,and may be useful to many practical control applications,such as tracking control in mechanical systems.And the effectiveness of the approach is demonstrated by a simulation example. 展开更多
关键词 Approximation model exponentially bounded sampled-data observer stochastic nonlinear
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Sampled-data extended state observer for uncertain nonlinear systems 被引量:1
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作者 Chuan TIAN Peng YAN Zhen ZHANG 《Control Theory and Technology》 EI CSCD 2016年第3期189-198,共10页
In this paper, we present a sampled-data nonlinear extended state observer (NLESO) design method for a class of nonlinear systems with uncertainties and discrete time output measurement. To accommodate the inter-sam... In this paper, we present a sampled-data nonlinear extended state observer (NLESO) design method for a class of nonlinear systems with uncertainties and discrete time output measurement. To accommodate the inter-sample dynamics, an inter-sample output predictor is employed in the structure of the NLESO to estimate the system output in the sampling intervals, where the prediction is used in the proposed observer instead of the system output. The exponential convergence of the sampled-data NLESO is also discussed and a sufficient condition is given by the Lyapunov method. A numerical example is provided to illustrate the performance of the proposed observer. 展开更多
关键词 SAMPLED-data extended state observer nonlinear systems
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TESTING FOR VARYING DISPERSION OF LONGITUDINAL BINOMIAL DATA IN NONLINEAR LOGISTIC MODELS WITH RANDOM EFFECTS 被引量:2
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作者 林金官 韦博成 《Acta Mathematica Scientia》 SCIE CSCD 2004年第4期559-568,共10页
In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. O... In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)). 展开更多
关键词 Longitudinal binomial data logistic regression nonlinear models power calculation random effects score test varying dispersion
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Stabilization for nonlinear systems via a limited capacity communication channel with data packet dropout
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作者 Lei ZHOU Guoping LU 《控制理论与应用(英文版)》 EI 2010年第1期111-116,共6页
This paper addresses the stabilization problem for a class of nonlinear systems. It is assumed that the controller can only receive the transmitted sequence of finite coded signals via a limited digital communication ... This paper addresses the stabilization problem for a class of nonlinear systems. It is assumed that the controller can only receive the transmitted sequence of finite coded signals via a limited digital communication channel. Both state and output feedback coder-decoder-controller procedures are proposed. Stabilization conditions involving the size of coding alphabet, the sampling period, system state growth rate and data packet dropout rate are obtained. Finally, an example is given to illustrate the design procedures and effectiveness of the proposed results. 展开更多
关键词 STABILIZATION nonlinear system Limited information data packet dropout Linear matrix inequality
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Global sampled-data output feedback control for a class of feedforward nonlinear systems
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作者 Zhihui WANG Junyong ZHAI Shumin FEI 《Control Theory and Technology》 EI CSCD 2014年第2期147-153,共7页
This paper investigates the problem of global output feedback stabilization for a class of feedforward nonlinear systems via linear sampled-data control. To solve the problem, we first construct a linear sampled-data ... This paper investigates the problem of global output feedback stabilization for a class of feedforward nonlinear systems via linear sampled-data control. To solve the problem, we first construct a linear sampled-data observer and controller. Then, a scaling gain is introduced into the proposed observer and controller. Finally, we use the sampled-data output feedback domination approach to find the explicit formula for choosing the scaling gain and the sampling period which renders the closed-loop system globally asymptotically stable. A simulation example is given to demonstrate the effectiveness of the proposed design procedure. 展开更多
关键词 Sampled-data control Global asymptotic stabilization Output feedback Feedforward nonlinear systems
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Calibration of Four Nonlinear Failure Envelopes from Triaxial Test Data and Influence of Nonlinearity on Geotechnical Computations
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作者 Amaechi J. Anyaegbunam Fidelis O. Okafor 《Geomaterials》 2021年第2期42-57,共16页
It is now recognized that many geomaterials have nonlinear failure envelopes. This non-linearity is most marked at lower stress levels, the failure envelope being of quasi-parabolic shape. It is not easy to calibrate ... It is now recognized that many geomaterials have nonlinear failure envelopes. This non-linearity is most marked at lower stress levels, the failure envelope being of quasi-parabolic shape. It is not easy to calibrate these nonlinear failure envelopes from triaxial test data. Currently only the power-type failure envelope has been studied with an established formal procedure for its determination from triaxial test data. In this paper, a simplified procedure is evolved for the development of four different types of nonlinear envelopes. These are of invaluable assistance in the evaluation of true factors of safety in problems of slope stability and correct computation of lateral earth pressure and bearing capacity. The use of the Mohr-Coulomb failure envelopes leads to an overestimation of the factors of safety and other geotechnical quantities. 展开更多
关键词 Calibration of nonlinear Failure Envelope Triaxial Test data Modified Maksimovic Envelope Power-Type Envelope Polynomial-Type Envelope Hoek-Brown Envelope Standard Error of Estimate
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THE STATE SPACE RECONSTRUCTION TECHNOLOGY OF DIFFERENT KINDS OF CHAOTIC DATA OBTAINED FROM DYNAMICAL SYSTEM 被引量:4
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作者 陈予恕 马军海 刘曾荣 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 1999年第1期82-92,共11页
Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a ... Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a theorem of Takens draws on the ideas from the generalized theory of information known as singular system analysis. We illustrate this technique by numerical data from the chaotic region of the chaotic experimental data. The method of the singular-value decomposition is used to calculate the eigenvalues of embedding space matrix. The corresponding concrete algorithm to calculate eigenvectors and to obtain the basis of embedding vector space is proposed in this paper. The projection on the orthogonal basis generated by eigenvectors of timeseries data and concrete paradigm are also provided here. Meanwhile the state space reconstruction technology of different kinds of chaotic data obtained from dynamical system has also been discussed in detail. 展开更多
关键词 nonlinear chaotic data embedding space matrix eigenvalue and eigenvector state space reconstruction
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Empirical data decomposition and its applications in image compression 被引量:2
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作者 Deng Jiaxian Wu Xiaoqin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2007年第1期164-170,共7页
A nonlinear data analysis algorithm, namely empirical data decomposition (EDD) is proposed, which can perform adaptive analysis of observed data. Analysis filter, which is not a linear constant coefficient filter, i... A nonlinear data analysis algorithm, namely empirical data decomposition (EDD) is proposed, which can perform adaptive analysis of observed data. Analysis filter, which is not a linear constant coefficient filter, is automatically determined by observed data, and is able to implement multi-resolution analysis as wavelet transform. The algorithm is suitable for analyzing non-stationary data and can effectively wipe off the relevance of observed data. Then through discussing the applications of EDD in image compression, the paper presents a 2-dimension data decomposition framework and makes some modifications of contexts used by Embedded Block Coding with Optimized Truncation (EBCOT) . Simulation results show that EDD is more suitable for non-stationary image data compression. 展开更多
关键词 Image processing Image compression Empirical data decomposition NON-STATIONARY nonlinear data decomposition framework
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Ensemble-based Kalman Filters in Strongly Nonlinear Dynamics 被引量:1
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作者 Zhaoxia PU Joshua HACKER 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2009年第3期373-380,共8页
This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that o... This study examines the effectiveness of ensemble Kalman filters in data assimilation with the strongly nonlinear dynamics of the Lorenz-63 model, and in particular their use in predicting the regime transition that occurs when the model jumps from one basin of attraction to the other. Four configurations of the ensemble-based Kalman filtering data assimilation techniques, including the ensemble Kalman filter, en- semble adjustment Kalman filter, ensemble square root filter and ensemble transform Kalman filter, are evaluated with their ability in predicting the regime transition (also called phase transition) and also are compared in terms of their sensitivity to both observational and sampling errors. The sensitivity of each ensemble-based filter to the size of the ensemble is also examined. 展开更多
关键词 ensemble Kalman filter nonlinear data assimilation Lorenz model
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Detecting Stationarity and Nonlinearity in Propeller Singing Signal
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作者 于大鹏 赵德有 汪玉 《Journal of Shanghai Jiaotong university(Science)》 EI 2010年第4期447-450,共4页
The propeller singing is such a complex fluid-structure coupling phenomenon that needs to study intensively. In this paper, the stationarity of propeller singing signal is tested by the recurrence plot technique. Acco... The propeller singing is such a complex fluid-structure coupling phenomenon that needs to study intensively. In this paper, the stationarity of propeller singing signal is tested by the recurrence plot technique. According to surrogate data, the singing time series has nonlinearity character. And the nonlinearity of time series is not caused by the static nonlinear measurement function but the intrinsic character itself based on further research. The results provide an objective basis for analyzing the propeller singing signal with the nonlinear time series technique 展开更多
关键词 propeller singing signal stationarity test nonlinearity test surrogate data
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Parameter estimation for dual-rate sampled Hammerstein systems with dead-zone nonlinearity 被引量:1
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作者 WANG Hongwei CHEN Yuxiao 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2020年第1期185-193,共9页
The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by... The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems. 展开更多
关键词 dual-rate sampled data dead-zone nonlinearity Hammerstein model system identification convergence analysis
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Nonlinear Analyses of Exchange Rates of Six Emerging Markets
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作者 雷强 潘英丽 《Journal of Shanghai Jiaotong university(Science)》 EI 2012年第1期108-113,共6页
This paper presents some empirical evidences on the presence of nonlinearity of exchange rates of six emerging markets by using Brock-Dechert-Scheinkman(BDS)test and Volterra-Wiener-Korenberg(VWK)model,respectively.Th... This paper presents some empirical evidences on the presence of nonlinearity of exchange rates of six emerging markets by using Brock-Dechert-Scheinkman(BDS)test and Volterra-Wiener-Korenberg(VWK)model,respectively.The nonlinear dependences are found in the exchange rates of six emerging markets.Furthermore,this paper applies the VWK model with surrogate data method to detect if their nonlinear dependences are deterministic or not.The results show that the above exchange rates are deterministic and nonlinear time series.These imply that the exchange rate markets do not conform to the requirements of the random walk hypothesis.Therefore,the nonlinear dynamic model should be used to analyze the exchange rates. 展开更多
关键词 Brock-Dechert-Scheinkman(BDS)test Volterra-Wiener-Korenberg(VWK)model nonlinearITY surrogate data exchange rate
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Asymptotic Calculation of the Wave Trough Exceedance Probabilities in A Nonlinear Sea 被引量:1
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作者 WANG Ying-guang 《China Ocean Engineering》 SCIE EI CSCD 2018年第2期189-195,共7页
This paper concerns the calculation of the wave trough exceedance probabilities in a nonlinear sea. The calculations have been carried out by incorporating a second order nonlinear wave model into an asymptotic method... This paper concerns the calculation of the wave trough exceedance probabilities in a nonlinear sea. The calculations have been carried out by incorporating a second order nonlinear wave model into an asymptotic method. This is a new approach for the calculation of the wave trough exceedance probabilities, and, as all of the calculations are performed in the probability domain, avoids the need for long time-domain simulations. The proposed asymptotic method has been applied to calculate the wave trough depth exceedance probabilities of a sea state with the surface elevation data measured at the coast of Yura in the Japan Sea. It is demonstrated that the proposed new method can offer better predictions than the theoretical Rayleigh wave trough depth distribution model. The calculated results by using the proposed new method have been further compared with those obtained by using the Arhan and Plaisted nonlinear distribution model and the Toffoli et al.’s wave trough depth distribution model, and its accuracy has been once again substantiated. The research findings obtained from this study demonstrate that the proposed asymptotic method can be readily utilized in the process of designing various kinds of ocean engineering structures. 展开更多
关键词 wave trough depth second order nonlinear wave model asymptotic method measured data
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Local Curvature and Centering Effects in Nonlinear Regression Models
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作者 Michael Brimacombe 《Open Journal of Statistics》 2016年第1期76-84,共9页
The effects of centering response and explanatory variables as a way of simplifying fitted linear models in the presence of correlation are reviewed and extended to include nonlinear models, common in many biological ... The effects of centering response and explanatory variables as a way of simplifying fitted linear models in the presence of correlation are reviewed and extended to include nonlinear models, common in many biological and economic applications. In a nonlinear model, the use of a local approximation can modify the effect of centering. Even in the presence of uncorrelated explanatory variables, centering may affect linear approximations and related test statistics. An approach to assessing this effect in relation to intrinsic curvature is developed and applied. Mis-specification bias of linear versus nonlinear models also reflects this centering effect. 展开更多
关键词 nonlinear Regression Centering data Model Mis-Specification BIAS CURVATURE
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