Distributed weighted least-squares estimation with fast convergence for large-scale systems

Weighted Least Squares Estimation with Missing Data

On Solving Large-Scale Weighted Least Squares Problems

A sequence of least squares problems of the form miny kG 1=2 (A T y ? h)k2 where G is an n n positive deenite diagonal weight matrix, and A an m n (m < n) sparse matrix with some dense columns; has many applications in linear programming, electrical networks, elliptic boundary value problems, and structural analysis. We discuss a technique for forming low-rank correction pre-conditioners for su...

Solution of large-scale weighted least-squares problems

A sequence of least squares problems of the form miny kG1=2(AT y h)k2, where G is an n n positive definite diagonal weight matrix, and A anm n (m n) sparse matrix with some dense columns; has many applications in linear programming, electrical networks, elliptic boundary value problems, and structural analysis. We suggest low-rank correction preconditioners for such problems, and a mixed solver...

Fast solving of weighted pairing least-squares systems

This paper presents a generalization of the "weighted least-squares" (WLS), named "weighted pairing least-squares" (WPLS), which uses a rectangular weight matrix and is suitable for data alignment problems. Two fast solving methods, suitable for solving full rank systems as well as rank deficient systems, are studied. Computational experiments clearly show that the best method, in terms of spee...

Empirical Distributions in Least Squares Estimation for Distributed Parameter Systems

We consider the estimation of error distributions in least squares identiication of distributed parameter systems. Asymptotic properties of approximate error sequences are developed. In particular, we examine consistency and asymptotic normality of empirical estimates of the error distribution. The consistency obtained is analogous to the Glivenko-Cantelli theorem. For asymptotic normality, we ...