Seemingly unrelated regression model with unequal size observations: computational aspects

Authors:
Paolo Foschi;Erricos J. Kontoghiorghes
Affiliations:
Institut d'informatique, Université de Neuchítel, ímile-Argand 11, Case Postal 2, CH-2007 Neuchítel, Switzerland;Institut d'informatique, Université de Neuchítel, ímile-Argand 11, Case Postal 2, CH-2007 Neuchítel, Switzerland
Venue:
Computational Statistics & Data Analysis
Year:
2002

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Abstract

The computational solution of the seemingly unrelated regression model with unequal size observations is considered. Two algorithms to solve the model when treated as a generalized linear least-squares problem are proposed. The algorithms have as a basic tool the generalized QR decomposition (GQRD) and efficiently exploit the block-sparse structure of the matrices. One of the algorithms reduces the computational burden of the estimation procedure by not computing explicitly the RQ factorization of the GQRD. The maximum likelihood estimation of the model when the covariance matrix is unknown is also considered.