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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 weighted total least-squares adjustment for linear regression
Journal of Geodesy, 2007The 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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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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Location and estimation of multiple outliers in weighted total least squares
Measurement, 2021Abstract Although the weighted total least squares (WTLS) adjustment is a rigorous method for estimating parameters in errors-in-variables (EIV) models, its solution is unreliable if the design matrix and/or observations contain multiple outliers.
Jianmin Wang +3 more
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An iterative solution of weighted total least-squares adjustment
Journal of Geodesy, 2010Total least-squares (TLS) adjustment is used to estimate the parameters in the errors-in-variables (EIV) model. However, its exact solution is rather complicated, and the accuracies of estimated parameters are too difficult to analytically compute. Since the EIV model is essentially a non-linear model, it can be solved according to the theory of non ...
Yunzhong Shen, Bofeng Li, Yi Chen
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On the Covariance Matrix of Weighted Total Least-Squares Estimates
Journal of Surveying Engineering, 2016AbstractThree strategies are employed to estimate the covariance matrix of the unknown parameters in an error-in-variable model. The first strategy simply computes the inverse of the normal matrix of the observation equations, in conjunction with the standard least-squares theory.
A. R. Amiri-Simkooei +2 more
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Total least squares linear prediction for frequency estimation with frequency weighting
1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002This paper presents a general total least squares (GTLS) solution for linear prediction to estimate closely spaced sinusoids. It is found that the TLS prediction error is not a good criterion to provide a robust solution. In this paper, a frequency weighted prediction error approach is introduced.
Shu Hung Leung +2 more
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