Observation systems known as errors-in-variables (EIV) models with model parameters estimated by total least squares (TLS) have been discussed for more than a century, though the terms EIV and TLS were coined much more recently. So far, it has only been shown that the inequality-constrained TLS (ICTLS) solution can be obtained by the combinatorial methods, assuming that the weight matrices of observations involved in the data vector and the data matrix are identity matrices. Although the previous works test all combinations of active sets or solution schemes in a clear way, some aspects have received little or no attention such as admissible weights, solution characteristics and numerical efficiency.
Fang, X. On non-combinatorial weighted total least squares with inequality constraints,
Springer Berlin Heidelberg, 2014, с. 805-816.
Fang, X. .
On non-combinatorial weighted total least squares with inequality constraints.
: Springer Berlin Heidelberg, 2014, с. 805-816.
Fang, X. (2014)
On non-combinatorial weighted total least squares with inequality constraints,
: Springer Berlin Heidelberg, с. 805-816
Fang, X.
(2014).
On non-combinatorial weighted total least squares with inequality constraints. Journal of Geodesy. Springer Berlin Heidelberg 88 (8), с. 805-816.
