A parallel approach for determining confidence intervals of variable statistics in large and sparse linear equations with RHS ranges
DOI10.1080/00207160701689534zbMath1165.65309OpenAlexW2145418633MaRDI QIDQ3630039
Publication date: 2 June 2009
Published in: International Journal of Computer Mathematics (Search for Journal in Brave)
Full work available at URL: http://www.informaworld.com/smpp/./content~db=all~content=a793267221
algorithmnumerical examplescovariance matrixparallel computinglinear programming methoddomain decompositionslarge and sparse systemsstatistical confidence intervals
Parametric tolerance and confidence regions (62F25) Computational methods for sparse matrices (65F50) Large-scale problems in mathematical programming (90C06) Linear programming (90C05) Parallel numerical computation (65Y05) Direct numerical methods for linear systems and matrix inversion (65F05)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Data distributions for sparse matrix vector multiplication
- The simplex method. A probabilistic analysis
- A parallel solver for large-scale Markov chains
- Conjugate gradient and Lanczos methods for sparse matrices on distributed memory multiprocessors
- A faster algorithm for solving linear algebraic equations on the star graph.
- Parallel scheduling of the PCG method for banded matrices rising from FDM/FEM.
- Efficient parallel solutions of linear algebraic circuits
- Parallel Algorithms for Dense Linear Algebra Computations
- Iterative algorithms for solution of large sparse systems of linear equations on hypercubes
- Parallel Matrix and Graph Algorithms
- A Survey of Parallel Algorithms in Numerical Linear Algebra
- Sparse Matrix Computations on Parallel Processor Arrays
- An Efficient Parallel Algorithm for the Solution of a Tridiagonal Linear System of Equations
- Fast parallel direct solvers for coarse grid problems
- Experimental evaluation of automatic array alignment in parallelized matlab
