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Shalabh : Optimality of Quasi-Score in the multivariate mean-variance model with an application to the zero-inflated Poisson model with measurement errors
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kukush, Alexander Malenko, Andrii Schneeweiß, Hans Shalabh |
| Copyright Year | 2007 |
| Abstract | In a multivariate mean-variance model, the class of linear score (LS) estimators based on an unbiased linear estimating function is introduced. A special member of this class is the (extended) quasi-score (QS) estimator. It is “extended” in the sense that it comprises the parameters describing the distribution of the regressor variables. It is shown that QS is (asymptotically) most efficient within the class of LS estimators. An application is the multivariate measurement error model, where the parameters describing the regressor distribution are nuisance parameters. A special case is the zero-inflated Poisson model with measurement errors, which can be treated within this framework. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://epub.ub.uni-muenchen.de/1992/1/paper_498.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Aclarubicin Arabic numeral 0 Errors-in-variables models Estimated Free variables and bound variables Generalization (Psychology) Least squares Log-linear model Observable Population Parameter Sample Variance Simulation |
| Content Type | Text |
| Resource Type | Article |
