Results 241 to 250 of about 90,279 (294)
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Survey Review, 2016
A mixed weighted least squares (WLS) and weighted total least squares (WTLS) (mixed WLS–WTLS) method is presented for an errors-in-variables (EIV) model with some fixed columns in the design matrix. The numerical computational scheme and an approximate accuracy assessment method are also provided.
Y. Zhou, X. Fang
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A mixed weighted least squares (WLS) and weighted total least squares (WTLS) (mixed WLS–WTLS) method is presented for an errors-in-variables (EIV) model with some fixed columns in the design matrix. The numerical computational scheme and an approximate accuracy assessment method are also provided.
Y. Zhou, X. Fang
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On weighted total least-squares adjustment for linear regression
Journal of Geodesy, 2007 The weighted total least-squares solution (WTLSS) is presented for an errors-in-variables model with fairly general variance–covariance matrices. In particular, the observations can be heteroscedastic and correlated, but the variance–covariance matrix of the dependent variables needs to have a certain block structure.
Burkhard Schaffrin, Andreas Wieser
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Web image interpolation via weighted total least squares regression
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012 Although ordinary least squares (OLS) regression achieves great success in clean image interpolation, its effectiveness is questionable in the scenario of web images which are usually compressed beforehand. The inherent flaw of OLS is that it is asymmetric, the perturbation is only confined on the right side of the linear system.
Xianming Liu 0005 +4 more
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On weighted total least-squares for geodetic transformations
Journal of Geodesy, 2011In this contribution, it is proved that the weighted total least-squares (WTLS) approach preserves the structure of the coefficient matrix in errors-in-variables (EIV) model when based on the perfect description of the dispersion matrix. To achieve this goal, first a proper algorithm for WTLS is developed since the quite recent analytical solution for ...
Vahid Mahboub, Mohammad Ali Sharifi
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On the weighting method for mixed least squares–total least squares problems
Numerical Linear Algebra with Applications, 2017SummaryIt is well known that the standard algorithm for the mixed least squares–total least squares (MTLS) problem uses the QR factorization to reduce the original problem into a standard total least squares problem with smaller size, which can be solved based on the singular value decomposition (SVD).
Qiaohua Liu, Minghui Wang
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Enhancement of Computational Efficiency for Weighted Total Least Squares
Journal of Surveying Engineering, 2021AbstractWeighted total least-squares (WTLS) adjustment is a rigorous method used for estimating parameters in the errors-in-variables (EIV) model.
Jianmin Wang +3 more
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A modified iterative algorithm for the weighted total least squares
Acta Geodaetica et Geophysica, 2020In this paper first, the method used for solving the weighted total least squares is discussed in two cases; (1) The parameter corresponding to the erroneous column in the design matrix is a scalar, model $$({\mathbf{H}} + {\mathbf{G}})^{T} {\mathbf{r}} + \delta \, = {\mathbf{q}} + {\mathbf{e}}$$, (2) The parameter corresponding to the erroneous column
Younes Naeimi, Behzad Voosoghi
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Weighted total least-squares joint adjustment with weight correction factors
Communications in Statistics - Simulation and Computation, 2018A joint adjustment involves integrating different types of geodetic datasets, or multiple datasets of the same data type, into a single adjustment.
Leyang Wang, Hang Yu
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On the Weighted Total Least Squares Solutions
2014Nowadays the terminology Total Least Squares (TLS) is frequently used as a standard name of the estimation method for the errors-in-variables (EIV) model. Although a significant number of contribution have been published to adjust the EIV model, the computational advantages of the TLS problem are still largely unknown.
X. Fang, H. Kutterer
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Iterative algorithm for weighted total least squares adjustment
Survey Review, 2013In this contribution, an iterative algorithm is developed for parameter estimation in a nonlinear measurement error model y2e5(A2EA)x, which is based on the complete description of the variance–covariance matrices of the observation errors e and of the coefficient matrix errors EA without any restriction, e.g.
S. Jazaeri +2 more
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