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https://hdl.handle.net/20.500.14279/2142| Title: | A comparative study of algorithms for solving seemingly unrelated regressions models | Authors: | Belsley, David A. Foschi, Paolo Kontoghiorghes, Erricos John |
metadata.dc.contributor.other: | Κοντογιώργης, Έρρικος Γιάννης | Major Field of Science: | Social Sciences | Field Category: | Economics and Business | Keywords: | Regression analysis;Algorithms;Problem solving | Issue Date: | 28-Oct-2003 | Source: | Computational Statistics and Data Analysis, 2003, vol. 44, no. 1-2, pp. 3-35 | Volume: | 44 | Issue: | 1-2 | Start page: | 3 | End page: | 35 | Journal: | Computational Statistics and Data Analysis | Abstract: | The computational efficiency of various algorithms for solving seemingly unrelated regressions (SUR) models is investigated. Some of the algorithms adapt known methods; others are new. The first transforms the SUR model to an ordinary linear model and uses the QR decomposition to solve it. Three others employ the generalized QR decomposition to solve the SUR model formulated as a generalized linear least-squares problem. Strategies to exploit the structure of the matrices involved are developed. The algorithms are reconsidered for solving the SUR model after it has been transformed to one of smaller dimensions. | URI: | https://hdl.handle.net/20.500.14279/2142 | ISSN: | 1679473 | DOI: | 10.1016/S0167-9473(03)00028-8 | Rights: | © Elsevier | Type: | Article | Affiliation : | Université de Neuchâtel | Publication Type: | Peer Reviewed |
| Appears in Collections: | Άρθρα/Articles |
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