least-squares estimation problem
Source term estimation of pollution from an instantaneous point source
... The approach taken was to develop the inverse model as a non-linear least squares estimation problem in which the source term was estimated using pollution concentration measurements on [r] ...
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AIC under the framework of least squares estimation
... parameter estimation in the framework of a least squares estimation problem ([10] and all the references ...the least squares ...the problem, the appropriate ...
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Ordinary Least Squares Estimation of a Dynamic Game Model
... at least two reasons why the estimation of dynamic games can be ...single-agent problem, it involves value functions that generally do not have closed-form and need to be numerically evaluated so it ...
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Least squares estimation of probability measures in the Prohorov metric framework
... (compare [15, 20, 28]) though some of the assumptions may be difficult to verify in practice. Assumptions (A3)–(A5) are mathematical in nature and may be verified directly for each specific problem. Assumptions ...
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Particle Swarm Optimization and Differentiation Evolution –Based Weighted Least Squares State Estimation
... State Estimation is one of the functions performed in the modern control ....State estimation (SE) is the backbone of energy management system (EMS) by playing important role of monitoring and control of ...
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Least squares estimation of hydraulic conductivity from field data
... wise or distributed observations. In general one expects k to be discontinuous (due, e.g., to lay- ering in the subsurface), and it is not known a priori where these discontinuities lie. Thus, in the inverse ...
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Consistent least squares fitting of ellipsoids
... A statistical point of view on the ellipsoid fitting problem is taken in [Kan94] and [CM96]. Kanatani proposed an unbiased estimation method, called a renormalization procedure. He uses an adjustment ...
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Particle swarm optimization and least squares estimation of NARMAX
... The results suggest that PSO’s swarm-based searching method and numerical-based methods (NE, QR and SVD) are quite similar with minor improvements in correlation violations and MSE values. Therefore, it can be concluded ...
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Solving Nonlinear Least Squares Problem Using Gauss-Newton Method
... likelihood estimation and least squares approach ...of least squares is a standard method to approximate the solution of over determined ...systems. Least squares is ...
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The design of parallel least squares model based on the surface fitting problem
... the least square parameter estimation of parallel algorithm from parameter estimation, Zhixia Yang presents a new parallel algorithm in linear problem, Deren Wang puts forward some solutions ...
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The element wise weighted total least squares problem
... parameter estimation problem is typically defined as an optimization problem: an appropriate cost function depending on the data is minimized over the estimated param- ...the ...
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Nonlinear Least Squares Estimation of the Shifted Gompertz Distribution
... moments, the method of percentiles and the Bayesian method. But, since each of these methods has some advantages and disadvantages, several other methods are proposed to estimate the unknown parameters in the shifted ...
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A Least-squares Approach to Direct Importance Estimation
... numerical problem tends to be severe if there are many change points in the regularization ...this problem, we develop an approximation algorithm in the same least-squares ...
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Empirical distributions in least squares estimation for distributed parameter systems
... nonlinear least squares problem was examined within the context of hypothesis testing for parameter ...the least squares residuals obtained by dierent ...
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Least squares estimation of a shift in linear processes
... The problem of a mean shift with an unknown shift point in an independent and identically distributed sequence has received considerable attention in the ...the estimation of the shift point in a sequence ...
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Using Least Squares Support Vector Machines for Frequency Estimation
... Frequency estimation is transformed to a pattern recognition problem, and a least squares support vector machine (LS-SVM) estimator is ...the estimation performance is insensitive to ...
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Some problems in adaptive estimation
... ast squares, is described in chapter ...ast squares, le ast squares, angular estimation and M-estimation are discussed in ...(location) problem is considered and asymptotic ...
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The search for a robust measure of road safety advertising effectiveness : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Marketing at Massey University, Palmerston North
... The models of the New Zealand campaign have varied in terms of, levels of data monthly, quarterly a nd yearly, estimation ordinary least squares, autoregression generalised least squares[r] ...
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Estimation and Inference in Unstable Nonlinear Least Squares Models (Final)
... stage least squares models by Hall, Han, and Boldea ...of estimation for general linear time series models is minimum description length (see Davis, Lee and Rodriguez-Yam, ...
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Burr type III Software Reliability Growth Model with Interval Domain Data
... popular estimation techniques are Maximum Likelihood Estimation (MLE) and Least Squares Estimation (LSE) (Goel, 1985; Ohba, ...MLE estimation by solving a set of simultaneous ...
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