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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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2020
<p>The errors-in-variables (EIV) model is applied to surveying and mapping fields such as empirical coordinate transformation, line/plane fitting and rigorous modelling of point clouds and so on as it takes the errors both in coefficient matrix and observation vector into account.
Xie Jian, Long Sichun
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<p>The errors-in-variables (EIV) model is applied to surveying and mapping fields such as empirical coordinate transformation, line/plane fitting and rigorous modelling of point clouds and so on as it takes the errors both in coefficient matrix and observation vector into account.
Xie Jian, Long Sichun
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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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Jackknife resample method for precision estimation of weighted total least squares
Communications in Statistics - Simulation and Computation, 2019Few studies have been conducted on the precision estimation of weighted total least squares (WTLS) by using the approximate function probability distribution method.
Leyang Wang, Fengbin Yu
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Weighted and structured sparse total least-squares for perturbed compressive sampling
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data vector as well as in the regression matrix. Weighted and structured generalizations of the TLS approach are further motivated in several signal processing and system ...
Hao Zhu 0001 +2 more
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Jackknife method for the location of gross errors in weighted total least squares
Communications in Statistics - Simulation and Computation, 2019AbstractBecause the weighted total least squares (WTLS) method lacks robustness and is sensitive to gross errors, it cannot eliminate the influence of outliers effectively.
Leyang Wang, Zhiqiang Li, Fengbin Yu
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A weighted total least-squares algorithm for fitting a straight line
Measurement Science and Technology, 2007The well-known problem of fitting a straight line to data with uncertainties in both coordinates is revisited. An algorithm is developed which treats x- and y-data in a symmetrical way. The problem is reduced to a one-dimensional search for a minimum.
M Krystek, M Anton
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Weighted total least squares applied to mixed observation model
Survey Review, 2016This contribution presents the weighted total least squares (WTLS) formulation for a mixed errors-in-variables (EIV) model, generally consisting of two erroneous coefficient matrices and two erroneous observation vectors. The formulation is conceptually simple because it is formulated based on the standard least squares theory.
A. R. Amiri-Simkooei +2 more
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