In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias es...In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.展开更多
Orthogonal projection methods have been widely used to solve linear systems. Little attention has been given to oblique projection methods, but the class of oblique projection methods is particularly attractive for la...Orthogonal projection methods have been widely used to solve linear systems. Little attention has been given to oblique projection methods, but the class of oblique projection methods is particularly attractive for large nonsymmetric systems. The purpose of this paper is to consider a criterion for judging whether a given appro ximation is acceptable and present an algorithm which computes an approximate solution to the linear systems Ax=b such that the normwise backward error meets some optimality condition.展开更多
文摘In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.
文摘Orthogonal projection methods have been widely used to solve linear systems. Little attention has been given to oblique projection methods, but the class of oblique projection methods is particularly attractive for large nonsymmetric systems. The purpose of this paper is to consider a criterion for judging whether a given appro ximation is acceptable and present an algorithm which computes an approximate solution to the linear systems Ax=b such that the normwise backward error meets some optimality condition.
