The WY representation for products of householder matrices
SIAM Journal on Scientific and Statistical Computing - Papers from the Second Conference on Parallel Processing for Scientific Computin
Seemingly unrelated regression equations models
Seemingly unrelated regression equations models
A storage-efficient WY representation for products of householder transformations
SIAM Journal on Scientific and Statistical Computing
Modifying the QR-decomposition to constrained and weighted line linear last squares
SIAM Journal on Matrix Analysis and Applications
Computational Statistics & Data Analysis
Matrix computations (3rd ed.)
Computational Economics - Special issue on computational economics in Geneva: volume 1: computational econometrics, statistics, and optimization
ScaLAPACK user's guide
Inconsistencies in SURE Models: Computational Aspects
Computational Economics - Special issue on computational studies at Cambridge
Estimation of VAR Models: Computational Aspects
Computational Economics
Parallel restricted maximum likelihood estimation for linear models with a dense exogenous matrix
Parallel Computing - Parallel matrix algorithms and applications
Computationally Efficient Methods for Solving SURE Models
NAA '00 Revised Papers from the Second International Conference on Numerical Analysis and Its Applications
Computationally efficient methods for estimating the updated-observations SUR models
Applied Numerical Mathematics
Multi-core CPUs, Clusters, and Grid Computing: A Tutorial
Computational Economics
Seemingly unrelated regression model with unequal size observations: computational aspects
Computational Statistics & Data Analysis
Hi-index | 0.00 |
The problem of computing estimates of parameters in SURE models withvariance inequalities and positivity of correlations constraintsis considered. Efficient algorithms that exploit the blockbi-diagonal structure of the data matrix are presented. Thecomputational complexity of the main matrix factorizations isanalyzed. A compact method to solve the model with proper subsetregressors is proposed.