Total Least-squares
Overview of total least squares methods
... the total least squares method also stimulated interest outside ...non-generic total least squares problems and proved that the proposed generalization still satisfies the ...
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On the equivalence between Total Least Squares and Maximum Likelihood PCA
... the total least squares (TLS) method has been generalized in the field of computational mathematics and engineering to maintain consistency of the parameter estimates in linear models with ...
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An adapted version of the element wise weighted total least squares method for applications in chemometrics
... This paper is an extension of paper [1]. In Ref. [1], it was shown that the Maximum Likelihood PCA (MLPCA) [2,3] method and the Element-wise Weighted Total Least Squares (EW-TLS) [4,5] method can be ...
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Consistency of the structured total least squares estimator in a multivariate errors in variables model
... A further generalization for the case when the rows of [ ˜ A B] ˜ have different covariance matrices (but are still mutually independent) is the element-wise weighted total least squares (EW-TLS) ...
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Application of structured total least squares for system identification and model reduction
... which of course does not imply that the STLS method is the only one that can treat identification problems, without input/output partitioning of the variables. In fact, we cite in the paper other methods that solve this ...
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Application of structured total least squares for system identification and model reduction
... global total least squares problem and alter- natively can be viewed as maximum likelihood identification in the errors-in-variables ...structured total least squares ...
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On the computation of the structured total least squares estimator
... structured total least squares problem is considered, in which the extended data matrix is partitioned into blocks and each of the blocks is Toeplitz = Hankel structured, unstructured, or noise ...
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A Quadratic Constraint Total Least squares Algorithm for Hyperbolic Location
... A novel TDOA based quadratic constraint total least- squares location algorithm is proposed in this paper. The proposed algorithm utilizes TLS to inhibit the influence of TDOA measurement errors. And ...
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Consistent least squares fitting of ellipsoids
... We point out several papers in which the ellipsoid fitting problem is considered. Gander et. al. [GGS94] consider algebraic and geometric fit- ting methods for circles and ellipses and note the inadequacy of the alge- ...
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The element wise weighted total least squares problem
... The total least-squares method yields an inconsistent estimate of the parameter in this ...Modified total least-squares problem, called element-wise weighted total ...
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On weighted structured total least squares
... Abstract. In this contribution we extend our previous results on the structured total least squares problem to the case of weighted cost func- tions. It is shown that the computational complexity of ...
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Block Toeplitz/Hankel structured total least squares
... structured total least squares problem is considered in which the extended data matrix is partitioned into blocks and each of the blocks is block-Toeplitz/Hankel structured, unstruc- tured, or ...
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3D Deformation Using Moving Least Squares
... Lewis et al. [Lewis et al. 2000] provides a summary of more tradi- tional deformation techniques, including the skeleton subspace de- formation (SSD), also known as skinning. SSD transforms a given point using a linear ...
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Least squares estimation of a shift in linear processes
... The least squares (LS) estimation of a shift is not new. Hawkins (1986) examined the LS method for a shift in an i.i.d. sequence. He proved that T 1/2−δ (ˆ τ − τ ) → 0 in probability for any δ > 0, where ...
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Distribution Theory of the Least Squares Averaging Estimator
... This paper derives the limiting distributions of least squares averaging estimators for linear regression models in a local asymptotic framework. We show that the averaging estimators with fixed weights are ...
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A note on approximating moments of least squares estimators
... We present results to facilitate the asymptotic approximation of the mo- ments of least squares coefficient estimators under similar assumptions to Phillips (2000), but focussing on the OLS estimator. The ...
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Least squares regret and partially strategic players
... apply least-squares regret to a number of well-known games, in particular, the Dollar Auction; Bertrand competition; inspection games; Matching Pennies; Chicken; coordination games; Battle of the Sexes; and ...
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An Error Controlled Method to Determine the Stellar Density Function in a Region of the Sky
... the least-squares method suffers from the deficiency that, its estimation procedure does not have detecting and controlling techniques for the sensitivity of the solution to the optimization criterion of ...
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Linear least squares localization in sensor networks
... Localization in sensor networks is critical for search and rescue. Linear least squares (LLS) estimation is a sub-optimum but low-complexity localization algorithm based on measurements of location-related ...
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Extremiles: a new perspective on asymmetric least squares
... This section shows that results for ordinary and trimmed extremiles are easily obtained by means of L-statistics theory. By contrast, asymmetric least squares estimation of high extremiles leads to ...
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