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Iterative weighted least-squares estimates in a heteroscedastic linear regression model |
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| Authors: | Kiyoshi Inoue |
| Institution: | Department of Economics, Faculty of Economics, Fukushima University, Kanayagawa 1, Fukushima-shi, Fukushima 960-1296, Japan |
| Abstract: | The aim of this study is to improve the efficiency of weighted least-squares estimates for a regression parameter. An iterative procedure, starting with an unbiased estimate other than the unweighted least-squares estimate, yields estimates which are asymptotically more efficient than the feasible generalized least-squares estimate when errors are spherically distributed. The result has an application in the improvement of the Graybill–Deal estimate of the common mean of several normal populations. |
| Keywords: | Heteroscedastic linear regression Iterative procedure Replication Asymptotic variance Common mean Graybill–Deal estimate Spherical distribution |
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