total least squares (TLS)
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 ...
14
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) ...
7
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 > ...
29
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 ...
16
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 ...
12
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) ...
44
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 ...
7
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 ...
5
Overview of total least squares methods
... classical total least squares method and describe algorithms for its generalization to weighted and structured approximation ...classical total least squares problem has a unique ...
24
Application of structured total least squares for system identification and model reduction
... which of course does not imply that the STLS method is the only one that can treat identification problems, without input/output partitioning of the variables. In fact, we cite in the paper other methods that solve this ...
6
Application of structured total least squares for system identification and model reduction
... The Total Least Squares Problem: Computational Aspects and Analysis (Philadelphia, PA: SIAM, 1991), and more than 130 papers in international journals and 140 conference ...
11
High performance numerical algorithms and software for structured total least squares
... We present a software package for structured total least-squares approximation problems. The allowed structures in the data matrix are block-Toeplitz, block-Hankel, unstructured, and exact. ...
21
On the computation of the structured total least squares estimator
... Unlike the methods mentioned above, which solve the STLS problem in its original for- mulation (4), the proposed methods solve an equivalent optimization problem, derived by analytically minimizing (4) over p , for a xed ...
18
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 ...
8
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 ...
17
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- ...
18
Teaching Least Squares in Matrix Notation
... least squares (WLS), also called homoskedastic and heteroskedastic regressions, are the names used to distinguish the special case of equal values for all standard deviations from the case of different ...
13
RLScore: Regularized Least-Squares Learners
... RLScore is a Python open source module for kernel based machine learning. The library provides implementations of several regularized least-squares (RLS) type of learners. RLS methods for regression and ...
5
Optimal Dictionary for Least Squares Representation
... The problem addressed in this article differs from the mainstream research of finding dictionaries offering sparse ( ` 0 -optimal) representations in the sense that our objective is to f[r] ...
28
Distributed Learning with Regularized Least Squares
... Here we only consider distributed learning with the regularized least squares. It would be of great interest and value to develop the theory for distributed learning with other algorithms such as spectral ...
31