Results 251 to 260 of about 525,476 (324)

Jackknife resample method for precision estimation of weighted total least squares

Communications in Statistics - Simulation and Computation, 2019
Few 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
semanticscholar   +2 more sources

On weighted total least-squares adjustment for linear regression

Journal of Geodesy, 2008
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.
B. Schaffrin, A. Wieser
semanticscholar   +2 more sources

On the Covariance Matrix of Weighted Total Least-Squares Estimates

Journal of Surveying Engineering, 2016
AbstractThree 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. Amiri-Simkooei, F. Zangeneh-Nejad, J. Asgari   +2 more
semanticscholar   +2 more sources

A robust weighted total least squares algorithm and its geodetic applications

Studia Geophysica et Geodaetica, 2016
Total least squares (TLS) can solve the issue of parameter estimation in the errors-invariables (EIV) model, however, the estimated parameters are affected or even severely distorted when the observation vector and coefficient matrix are contaminated by gross errors.
Bin Wang, Jiancheng Li, Chao Liu
semanticscholar   +2 more sources

Bias-Corrected Weighted Total Least-Squares Adjustment of Condition Equations

Journal of Surveying Engineering, 2015
The total least-squares (TLS) method and its variations have recently received increasing research attention. However, little attention has been given to the weighted TLS adjustment method with condition equations.
X. Tong, Yanmin Jin, Songlin Zhang, Lingyun Li, Shijie Liu   +4 more
semanticscholar   +2 more sources

New second order approximation method for posterior precision evaluation of weighted total least squares estimates with analytical expression

Communications in statistics. Simulation and computation, 2023
Several first order approximate methods to evaluate the posterior precision of weighted total least squares estimates have been developed but there is still some space for the methods of precision estimation.
Shimeng Dong, Songlin Zhang, Jie Han
semanticscholar   +1 more source

Median robust nonlinear weighted total least squares estimator of nonlinear EIV models: three algorithms

Survey Review, 2022
To improve robust estimation performance of fully correlated nonlinear error-in-variables model, three median robust estimate methods are discussed on base of Nonlinear Weighted Total Least Squares (NWTLS), namely, median parameter method, median ...
Chuan Hu, Chenghong Li, Chongyang Zhang, Lidu Zhao, Xiaomeng Fan, Yusen Zhou, Hongzhou Zhu, Zheng Chen   +7 more
semanticscholar   +1 more source

Weighted total least squares–Bayes filter-based estimation of relative pose for a space non-cooperative unknown target without a priori knowledge

Measurement science and technology, 2021
The estimation of relative pose of a space non-cooperative target is an attractive yet challenging task due to the complexity of the target background and illumination, and the lack of a priori knowledge.
Chengguang Zhu, Zhongpai Gao, Jiankang Zhao, Haihui Long, Chuanqi Liu   +4 more
semanticscholar   +1 more source

Weighted and partial total least squares method for the EIV model with linear equality and inequality constraints

Survey Review, 2023
A weighted and partial total least squares method for the errors-in-variables (EIV) model with linear equality and inequality constraints is presented. A collected observation vector is formed by the independent variables both in the observation vector ...
Yanmin Jin, Lizhou Sun, X. Tong, Shijie Liu, Yongjiu Feng, Sicong Liu   +5 more
semanticscholar   +1 more source

On the weighting method for mixed least squares–total least squares problems

Numerical Linear Algebra with Applications, 2017
SummaryIt 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
openaire   +1 more source