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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Total Least Squares Fitting the Three-Parameter Inverse Weibull Density
... the least squares method. The non- linear weighted ordinary least squares (OLS) fitting problem for the three-parameter inverse Weibull density is considered by Maruši´c et ...weighted ...
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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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High performance numerical algorithms and software for structured total least squares
... “structured total least squares” appeared only 23 years later in the literature ...nonlinear least-squares minimization methods for solving an equivalent unconstrained ...
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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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Application of structured total least squares for system identification and model reduction
... structured total least squares method for MIMO system identifi- cation, which is the main contribution of the paper, is ...structured total least squares method for system ...
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Adaptive matching pursuit with constrained total least squares
... the least squares model with total least squares (TLS) criterion, which is appro- priate to deal with the fitting problem when perturba- tions exist in both the measurement vector and ...
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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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An adapted version of the element wise weighted total least squares method for applications in chemometrics
... 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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Study the Behavior of Total Least Squares Technique in Adjusting GPS Field Data - A Case Study
... Abstract The main research fields in mathematical and satellite geodesy are computations and adjustment to assess the magnitude of errors and to study their distributions in terms of when they are within the adequate ...
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The element wise weighted total least squares problem
... ized total least-squares (GTLS) estimator, the errors D ˜ are assumed row-wise independent and correlated within the rows with identical covariance matrix V = V > ...
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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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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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Deformation analysis with Total Least Squares
... a Least Squares (LS) technique is used for the transforma- tion ...the Total Least Squares (TLS) that is considerably a new approach in geodetic ...the Least Squares (LS) ...
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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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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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Orthogonal least squares regression with tunable kernels
... A basic principle in practical nonlinear data modelling is the parsimonious principle of ensuring the smallest possible model that explains the training data. The existing sparse kernel modelling methods [1]–[6] place ...
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05_Linear_Regression_1.pdf
... Maximum Likelihood and Least Squares Geometry of Least Squares Sequential Learning Regularized Least Squares Multiple Outputs Loss Function for Regression The Bias-Variance Decomposition[r] ...
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Some aspects of progeny testing Southdown rams : a thesis presented in part fulfilment of the requirements for the degree of Master of Agricultural Science in Massey University of Manawatu, New Zealand
... Least squares means, least squares deviations of sire groups from the means, least squares differences due to birthrank and sex, and partial regression coefficients for the characteristi[r] ...
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Distributed Learning with Regularized Least Squares
... the least squares regularization scheme in a reproducing kernel Hilbert space ...the least squares regularization scheme to each data subset to produce an output function, and then takes an ...
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